run_clphobert_hackathon.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4DD12Ih9sZyv","executionInfo":{"status":"ok","timestamp":1726221531297,"user_tz":-420,"elapsed":1488,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"17541a9f-a3a0-4a6f-dfa2-6bb3d9f90652"},"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'ViNLU'...\n","remote: Enumerating objects: 1220, done.\u001b[K\n","remote: Counting objects: 100% (205/205), done.\u001b[K\n","remote: Compressing objects: 100% (118/118), done.\u001b[K\n","remote: Total 1220 (delta 116), reused 164 (delta 83), pack-reused 1015 (from 1)\u001b[K\n","Receiving objects: 100% (1220/1220), 4.26 MiB | 18.58 MiB/s, done.\n","Resolving deltas: 100% (772/772), done.\n"]}],"source":["!git clone https://github.com/phongtintruong/ViNLU.git\n"]},{"cell_type":"code","source":["%cd ViNLU"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"szgm7VCBsmJU","executionInfo":{"status":"ok","timestamp":1726221536339,"user_tz":-420,"elapsed":466,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"786b5051-a077-41d0-9757-13171f547508"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/ViNLU\n"]}]},{"cell_type":"code","source":["!git config user.name \"phongtintruong\"\n","!git config user.email \"trung.nt204857@sis.hust.edu.vn\""],"metadata":{"id":"l_AZa4D4tGIG","executionInfo":{"status":"ok","timestamp":1726221540875,"user_tz":-420,"elapsed":508,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["!git status"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"M9bYtGhCtKwc","executionInfo":{"status":"ok","timestamp":1726221545438,"user_tz":-420,"elapsed":545,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"05b9df47-6874-4525-9cae-5c69c4effc49"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["On branch main\n","Your branch is up to date with 'origin/main'.\n","\n","nothing to commit, working tree clean\n"]}]},{"cell_type":"code","source":["!pip install transformers pytorch-crf seqeval"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jSXElbj5tQGq","executionInfo":{"status":"ok","timestamp":1726077736394,"user_tz":-420,"elapsed":13466,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"f467e45e-31a6-499d-cb6b-0d4bdf697b1f"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.44.2)\n","Collecting pytorch-crf\n","  Downloading pytorch_crf-0.7.2-py3-none-any.whl.metadata (2.4 kB)\n","Collecting seqeval\n","  Downloading seqeval-1.2.2.tar.gz (43 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.6/43.6 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.16.0)\n","Requirement already satisfied: huggingface-hub<1.0,>=0.23.2 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.24.6)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.26.4)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (24.1)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.2)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2024.5.15)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.32.3)\n","Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.5)\n","Requirement already satisfied: tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.19.1)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.5)\n","Requirement already satisfied: scikit-learn>=0.21.3 in /usr/local/lib/python3.10/dist-packages (from seqeval) (1.3.2)\n","Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (2024.6.1)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (4.12.2)\n","Requirement already satisfied: scipy>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.21.3->seqeval) (1.13.1)\n","Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.21.3->seqeval) (1.4.2)\n","Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.21.3->seqeval) (3.5.0)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.8)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.8.30)\n","Downloading pytorch_crf-0.7.2-py3-none-any.whl (9.5 kB)\n","Building wheels for collected packages: seqeval\n","  Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for seqeval: filename=seqeval-1.2.2-py3-none-any.whl size=16161 sha256=0f2a9e8b16fb26a0604dbf13595e18068eba38844b5ab71808def162ab0df1db\n","  Stored in directory: /root/.cache/pip/wheels/1a/67/4a/ad4082dd7dfc30f2abfe4d80a2ed5926a506eb8a972b4767fa\n","Successfully built seqeval\n","Installing collected packages: pytorch-crf, seqeval\n","Successfully installed pytorch-crf-0.7.2 seqeval-1.2.2\n"]}]},{"cell_type":"code","source":["!ls"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"tmT0Jfiouyps","executionInfo":{"status":"ok","timestamp":1726077736776,"user_tz":-420,"elapsed":385,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"f0374e61-881c-494c-ea12-0f5018714d75"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["data_loader.py\t\t      run_jointBERT-CRF_PhoBERTencoder.sh\n","dataset_statistic.png\t      run_jointBERT-CRF_XLM-Rencoder.sh\n","early_stopping.py\t      run_jointIDSF_PhoBERTencoder_fromscratch.sh\n","Evaluation\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_01.sh\n","Hackathon\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_02.sh\n","JointModel.png\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_03.sh\n","LICENSE\t\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_04.sh\n","main.py\t\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_06.sh\n","Minh_ViNLU\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_07.sh\n","model\t\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_08.sh\n","PhoATIS\t\t\t      run_jointIDSF_PhoBERTencoder_idsf_lambda_09.sh\n","predict.py\t\t      run_jointIDSF_PhoBERTencoder.sh\n","predict.sh\t\t      run_jointIDSF_XLM-Rencoder.sh\n","README.md\t\t      RunScript\n","requirements.txt\t      trainer.py\n","run_baseline_hackathon.ipynb  utils.py\n"]}]},{"cell_type":"code","source":["# Setting environment variables in the notebook\n","lr = \"3e-5\"\n","c = \"0.8\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Setting up the MODEL_DIR variable\n","MODEL_DIR = f\"Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Running the python script using the converted bash command\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vAn94YOFtebQ","executionInfo":{"status":"ok","timestamp":1726078843008,"user_tz":-420,"elapsed":1081405,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"0f191f83-0b20-4329-8c6c-595dc05ade78"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["3e-5\n","Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100\n","2024-09-11 18:02:58.051726: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 18:02:58.091967: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 18:02:58.103840: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 18:02:58.130634: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 18:03:00.257257: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","tokenizer_config.json: 100% 1.17k/1.17k [00:00<00:00, 7.95MB/s]\n","vocab.txt: 100% 895k/895k [00:00<00:00, 10.7MB/s]\n","bpe.codes: 100% 1.14M/1.14M [00:00<00:00, 47.7MB/s]\n","added_tokens.json: 100% 22.0/22.0 [00:00<00:00, 141kB/s]\n","special_tokens_map.json: 100% 167/167 [00:00<00:00, 1.19MB/s]\n","09/11/2024 18:03:02 - INFO - data_loader -   Creating features from dataset file at Hackathon\n","09/11/2024 18:03:02 - INFO - data_loader -   LOOKING AT Hackathon/word-level/train\n","09/11/2024 18:03:02 - INFO - data_loader -   Writing example 0 of 1790\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: train-0\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> tăng bóng 3 26 phần_trăm </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 128 301 107 1742 8638 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 20 21 13 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: train-1\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> hãy tăng thêm độ sáng phòng ngủ con trai lên 91 phần_trăm </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 852 128 143 378 298 292 845 73 443 72 5588 8638 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 8 23 2 2 19 5 5 5 2 22 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: train-2\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> giúp mình tăng đèn âm trần thứ 2 lên 10 phần_trăm ở phòng con_nhỏ 4 tầng 5 nhé </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 171 68 128 1690 2226 2834 129 76 72 210 8638 25 292 6791 163 1032 173 2083 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 2 2 20 21 21 21 21 2 13 17 2 19 5 5 11 7 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: train-3\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> bạn có_thể tăng giúp mình bóng chùm thứ 3 lên mức 21 phần_trăm được không </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 88 62 128 171 68 301 6548 129 107 72 185 1298 8638 11 17 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 2 2 2 2 20 21 21 21 2 2 13 17 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: train-4\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> tăng bình_nóng_lạnh 5 phần_trăm </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 128 51476 173 8638 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 20 13 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   Saving features into cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 18:03:02 - INFO - data_loader -   Creating features from dataset file at Hackathon\n","09/11/2024 18:03:02 - INFO - data_loader -   LOOKING AT Hackathon/word-level/dev\n","09/11/2024 18:03:02 - INFO - data_loader -   Writing example 0 of 392\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: dev-0\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> anh ơi thiết_bị là đầy_đủ r@@ g@@ b 4 </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 83 3322 627 8 997 1698 1529 2774 163 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 2 (id = 2)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 2 2 2 2 20 0 0 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: dev-1\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> chào giảm giúp tôi đèn hoa trong phòng con </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 3683 197 171 70 1690 389 12 292 73 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 2 (id = 2)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 2 2 2 20 21 2 19 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: dev-2\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> làm_ơn hạ xuống đỡ đèn treo tường thứ 4 1 phần_trăm giúp tôi </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 43025 1269 307 3220 1690 2051 1897 129 163 99 8638 171 70 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 2 (id = 2)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 8 23 2 20 21 21 21 21 13 17 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: dev-3\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> tôi muốn giảm độ sáng của đèn ngủ 2 </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 70 202 197 378 298 7 1690 845 76 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 2 (id = 2)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 2 2 2 2 2 2 20 21 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:02 - INFO - data_loader -   guid: dev-4\n","09/11/2024 18:03:02 - INFO - data_loader -   tokens: <s> nút ấn 3 to quá giảm còn 18 phần_trăm giúp tôi </s>\n","09/11/2024 18:03:02 - INFO - data_loader -   input_ids: 0 2262 4903 107 889 204 197 50 890 8638 171 70 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:02 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   intent_label: 2 (id = 2)\n","09/11/2024 18:03:02 - INFO - data_loader -   slot_labels: 0 20 21 21 2 2 2 2 13 17 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:02 - INFO - data_loader -   Saving features into cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 18:03:03 - INFO - data_loader -   Creating features from dataset file at Hackathon\n","09/11/2024 18:03:03 - INFO - data_loader -   LOOKING AT Hackathon/word-level/test\n","09/11/2024 18:03:03 - INFO - data_loader -   Writing example 0 of 346\n","09/11/2024 18:03:03 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:03 - INFO - data_loader -   guid: test-0\n","09/11/2024 18:03:03 - INFO - data_loader -   tokens: <s> tăng giúp mình mức_độ của ốp tường thứ 1 lên với </s>\n","09/11/2024 18:03:03 - INFO - data_loader -   input_ids: 0 128 171 68 1653 7 7601 1897 129 99 72 15 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:03 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:03 - INFO - data_loader -   slot_labels: 0 2 2 2 2 2 20 21 21 21 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:03 - INFO - data_loader -   guid: test-1\n","09/11/2024 18:03:03 - INFO - data_loader -   tokens: <s> tôi muốn tăng đèn sắc_màu thứ 3 </s>\n","09/11/2024 18:03:03 - INFO - data_loader -   input_ids: 0 70 202 128 1690 6960 129 107 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:03 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:03 - INFO - data_loader -   slot_labels: 0 2 2 2 20 21 21 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:03 - INFO - data_loader -   guid: test-2\n","09/11/2024 18:03:03 - INFO - data_loader -   tokens: <s> tôi muốn tăng đèn cảnh 3 </s>\n","09/11/2024 18:03:03 - INFO - data_loader -   input_ids: 0 70 202 128 1690 805 107 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:03 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:03 - INFO - data_loader -   slot_labels: 0 2 2 2 20 21 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:03 - INFO - data_loader -   guid: test-3\n","09/11/2024 18:03:03 - INFO - data_loader -   tokens: <s> ch@@ oà bạn tôi muốn tăng mức_độ của bóng ốp trần thứ 1 </s>\n","09/11/2024 18:03:03 - INFO - data_loader -   input_ids: 0 1347 9638 88 70 202 128 1653 7 301 7601 2834 129 99 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:03 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:03 - INFO - data_loader -   slot_labels: 0 2 0 2 2 2 2 2 2 20 21 21 21 21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   *** Example ***\n","09/11/2024 18:03:03 - INFO - data_loader -   guid: test-4\n","09/11/2024 18:03:03 - INFO - data_loader -   tokens: <s> giúp mình tăng đèn vườn thứ 1 lên 2 phần_trăm tại phòng ngủ bố_mẹ tầng lầu thượng 4 nhé </s>\n","09/11/2024 18:03:03 - INFO - data_loader -   input_ids: 0 171 68 128 1690 1333 129 99 72 76 8638 35 292 845 1385 1032 8829 7899 163 2083 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n","09/11/2024 18:03:03 - INFO - data_loader -   attention_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   token_type_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   intent_label: 7 (id = 7)\n","09/11/2024 18:03:03 - INFO - data_loader -   slot_labels: 0 2 2 2 20 21 21 21 2 13 17 2 19 5 5 2 11 7 7 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n","09/11/2024 18:03:03 - INFO - data_loader -   Saving features into cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","config.json: 100% 748/748 [00:00<00:00, 4.62MB/s]\n","model.safetensors: 100% 540M/540M [00:05<00:00, 92.7MB/s]\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at phongtintruong/clphobert-base-16-256-50-30 and are newly initialized: ['crf.end_transitions', 'crf.start_transitions', 'crf.transitions', 'intent_classifier.linear.bias', 'intent_classifier.linear.weight', 'slot_classifier.linear.bias', 'slot_classifier.linear.weight', 'slot_classifier.linear_slot.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 18:03:09 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:03:09 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:03:09 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:03<00:00,  2.23it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: UNK seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 18:03:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:03:13 - INFO - trainer -     intent_acc = 0.07397959183673469\n","09/11/2024 18:03:13 - INFO - trainer -     loss = 9.533089910234724\n","09/11/2024 18:03:13 - INFO - trainer -     mean_intent_slot = 0.0422349498522328\n","09/11/2024 18:03:13 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 18:03:13 - INFO - trainer -     slot_f1 = 0.0104903078677309\n","09/11/2024 18:03:13 - INFO - trainer -     slot_precision = 0.006715328467153284\n","09/11/2024 18:03:13 - INFO - trainer -     slot_recall = 0.023958333333333335\n","{'loss': 9.533089910234724, 'intent_acc': 0.07397959183673469, 'slot_precision': 0.006715328467153284, 'slot_recall': 0.023958333333333335, 'slot_f1': 0.0104903078677309, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.0422349498522328}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 18:03:13 - INFO - trainer -   ***** Running training *****\n","09/11/2024 18:03:13 - INFO - trainer -     Num examples = 1790\n","09/11/2024 18:03:13 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 18:03:13 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 18:03:13 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 18:03:13 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 18:03:13 - INFO - trainer -     Logging steps = 56\n","09/11/2024 18:03:13 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:17<00:00,  3.32it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:03:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:03:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:03:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.33it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.41it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.38it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.91it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, msg_start, len(result))\n","09/11/2024 18:03:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:03:32 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 18:03:32 - INFO - trainer -     loss = 5.910099438258579\n","09/11/2024 18:03:32 - INFO - trainer -     mean_intent_slot = 0.4005102040816326\n","09/11/2024 18:03:32 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 18:03:32 - INFO - trainer -     slot_f1 = 0.0\n","09/11/2024 18:03:32 - INFO - trainer -     slot_precision = 0.0\n","09/11/2024 18:03:32 - INFO - trainer -     slot_recall = 0.0\n","mean_intent_slot increased (inf --> 0.400510).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.39it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:03:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:03:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:03:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 18:03:56 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:03:56 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 18:03:56 - INFO - trainer -     loss = 4.441436120441982\n","09/11/2024 18:03:56 - INFO - trainer -     mean_intent_slot = 0.4005102040816326\n","09/11/2024 18:03:56 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 18:03:56 - INFO - trainer -     slot_f1 = 0.0\n","09/11/2024 18:03:56 - INFO - trainer -     slot_precision = 0.0\n","09/11/2024 18:03:56 - INFO - trainer -     slot_recall = 0.0\n","mean_intent_slot increased (0.400510 --> 0.400510).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.21it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:17<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:04:20 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:04:20 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:04:20 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.04it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.07it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.12it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:04:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:04:22 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 18:04:22 - INFO - trainer -     loss = 2.686278428350176\n","09/11/2024 18:04:22 - INFO - trainer -     mean_intent_slot = 0.7057065977075762\n","09/11/2024 18:04:22 - INFO - trainer -     semantic_frame_acc = 0.1760204081632653\n","09/11/2024 18:04:22 - INFO - trainer -     slot_f1 = 0.6027397260273972\n","09/11/2024 18:04:22 - INFO - trainer -     slot_precision = 0.6666666666666666\n","09/11/2024 18:04:22 - INFO - trainer -     slot_recall = 0.55\n","mean_intent_slot increased (0.400510 --> 0.705707).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.54it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:18<00:00,  3.09it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:04:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:04:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:04:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.10it/s]\n","09/11/2024 18:04:44 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:04:44 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:04:44 - INFO - trainer -     loss = 1.7950106859207153\n","09/11/2024 18:04:44 - INFO - trainer -     mean_intent_slot = 0.7870609617237453\n","09/11/2024 18:04:44 - INFO - trainer -     semantic_frame_acc = 0.4336734693877551\n","09/11/2024 18:04:44 - INFO - trainer -     slot_f1 = 0.7424892703862661\n","09/11/2024 18:04:44 - INFO - trainer -     slot_precision = 0.7654867256637168\n","09/11/2024 18:04:44 - INFO - trainer -     slot_recall = 0.7208333333333333\n","mean_intent_slot increased (0.705707 --> 0.787061).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.29it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:17<00:00,  3.14it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:05:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:05:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:05:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:05:08 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:05:08 - INFO - trainer -     intent_acc = 0.875\n","09/11/2024 18:05:08 - INFO - trainer -     loss = 1.2378970214298792\n","09/11/2024 18:05:08 - INFO - trainer -     mean_intent_slot = 0.8349489795918368\n","09/11/2024 18:05:08 - INFO - trainer -     semantic_frame_acc = 0.5535714285714286\n","09/11/2024 18:05:08 - INFO - trainer -     slot_f1 = 0.7948979591836735\n","09/11/2024 18:05:08 - INFO - trainer -     slot_precision = 0.779\n","09/11/2024 18:05:08 - INFO - trainer -     slot_recall = 0.8114583333333333\n","mean_intent_slot increased (0.787061 --> 0.834949).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.53it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:05:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:05:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:05:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.46it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.54it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.98it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.06it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.47it/s]\n","09/11/2024 18:05:30 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:05:30 - INFO - trainer -     intent_acc = 0.8545918367346939\n","09/11/2024 18:05:30 - INFO - trainer -     loss = 1.061938145330974\n","09/11/2024 18:05:30 - INFO - trainer -     mean_intent_slot = 0.8486668861092824\n","09/11/2024 18:05:30 - INFO - trainer -     semantic_frame_acc = 0.5739795918367347\n","09/11/2024 18:05:30 - INFO - trainer -     slot_f1 = 0.842741935483871\n","09/11/2024 18:05:30 - INFO - trainer -     slot_precision = 0.81640625\n","09/11/2024 18:05:30 - INFO - trainer -     slot_recall = 0.8708333333333333\n","mean_intent_slot increased (0.834949 --> 0.848667).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.51it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:17<00:00,  2.97it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:05:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:05:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:05:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.59it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.62it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.60it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.57it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.76it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.25it/s]\n","09/11/2024 18:05:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:05:53 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:05:53 - INFO - trainer -     loss = 0.9478798338345119\n","09/11/2024 18:05:53 - INFO - trainer -     mean_intent_slot = 0.8615821264827888\n","09/11/2024 18:05:53 - INFO - trainer -     semantic_frame_acc = 0.5841836734693877\n","09/11/2024 18:05:53 - INFO - trainer -     slot_f1 = 0.8660213958227203\n","09/11/2024 18:05:53 - INFO - trainer -     slot_precision = 0.847457627118644\n","09/11/2024 18:05:53 - INFO - trainer -     slot_recall = 0.8854166666666666\n","mean_intent_slot increased (0.848667 --> 0.861582).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.52it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:06:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:06:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:06:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:06:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:06:15 - INFO - trainer -     intent_acc = 0.8596938775510204\n","09/11/2024 18:06:15 - INFO - trainer -     loss = 0.8893680966326168\n","09/11/2024 18:06:15 - INFO - trainer -     mean_intent_slot = 0.8739463176574978\n","09/11/2024 18:06:15 - INFO - trainer -     semantic_frame_acc = 0.6301020408163265\n","09/11/2024 18:06:15 - INFO - trainer -     slot_f1 = 0.8881987577639752\n","09/11/2024 18:06:15 - INFO - trainer -     slot_precision = 0.8827160493827161\n","09/11/2024 18:06:15 - INFO - trainer -     slot_recall = 0.89375\n","mean_intent_slot increased (0.861582 --> 0.873946).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.53it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:17<00:00,  3.14it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:06:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:06:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:06:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.04it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.09it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:06:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:06:37 - INFO - trainer -     intent_acc = 0.8545918367346939\n","09/11/2024 18:06:37 - INFO - trainer -     loss = 0.874052922640528\n","09/11/2024 18:06:37 - INFO - trainer -     mean_intent_slot = 0.8759278233750909\n","09/11/2024 18:06:37 - INFO - trainer -     semantic_frame_acc = 0.6377551020408163\n","09/11/2024 18:06:37 - INFO - trainer -     slot_f1 = 0.8972638100154879\n","09/11/2024 18:06:37 - INFO - trainer -     slot_precision = 0.8894575230296827\n","09/11/2024 18:06:37 - INFO - trainer -     slot_recall = 0.9052083333333333\n","mean_intent_slot increased (0.873946 --> 0.875928).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.17it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:17<00:00,  3.10it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:07:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:07:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:07:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.02it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.13it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:07:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:07:03 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:07:03 - INFO - trainer -     loss = 0.8628909225974765\n","09/11/2024 18:07:03 - INFO - trainer -     mean_intent_slot = 0.8746516519380338\n","09/11/2024 18:07:03 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 18:07:03 - INFO - trainer -     slot_f1 = 0.9304257528556595\n","09/11/2024 18:07:03 - INFO - trainer -     slot_precision = 0.927536231884058\n","09/11/2024 18:07:03 - INFO - trainer -     slot_recall = 0.9333333333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.82it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:17<00:00,  3.11it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:07:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:07:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:07:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.43it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.57it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.14it/s]\n","09/11/2024 18:07:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:07:23 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:07:23 - INFO - trainer -     loss = 0.8681467069046838\n","09/11/2024 18:07:23 - INFO - trainer -     mean_intent_slot = 0.8781789234746422\n","09/11/2024 18:07:23 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 18:07:23 - INFO - trainer -     slot_f1 = 0.914521112255407\n","09/11/2024 18:07:23 - INFO - trainer -     slot_precision = 0.9042769857433809\n","09/11/2024 18:07:23 - INFO - trainer -     slot_recall = 0.925\n","mean_intent_slot increased (0.875928 --> 0.878179).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.38it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:17<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:07:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:07:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:07:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:07:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:07:46 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:07:46 - INFO - trainer -     loss = 0.9102108515799046\n","09/11/2024 18:07:46 - INFO - trainer -     mean_intent_slot = 0.8779840156921663\n","09/11/2024 18:07:46 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 18:07:46 - INFO - trainer -     slot_f1 = 0.9243353783231083\n","09/11/2024 18:07:46 - INFO - trainer -     slot_precision = 0.9076305220883534\n","09/11/2024 18:07:46 - INFO - trainer -     slot_recall = 0.9416666666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.86it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:17<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:08:04 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:08:04 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:08:04 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.59it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.07it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.08it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.56it/s]\n","09/11/2024 18:08:06 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:08:06 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:08:06 - INFO - trainer -     loss = 0.8542170322367123\n","09/11/2024 18:08:06 - INFO - trainer -     mean_intent_slot = 0.879088981271521\n","09/11/2024 18:08:06 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 18:08:06 - INFO - trainer -     slot_f1 = 0.9393004115226338\n","09/11/2024 18:08:06 - INFO - trainer -     slot_precision = 0.9278455284552846\n","09/11/2024 18:08:06 - INFO - trainer -     slot_recall = 0.9510416666666667\n","mean_intent_slot increased (0.878179 --> 0.879089).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.53it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:08:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:08:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:08:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.07it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:08:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:08:28 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 18:08:28 - INFO - trainer -     loss = 1.0400749796203204\n","09/11/2024 18:08:28 - INFO - trainer -     mean_intent_slot = 0.8686614210676502\n","09/11/2024 18:08:28 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 18:08:28 - INFO - trainer -     slot_f1 = 0.9363024339720352\n","09/11/2024 18:08:28 - INFO - trainer -     slot_precision = 0.9309989701338826\n","09/11/2024 18:08:28 - INFO - trainer -     slot_recall = 0.9416666666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:17<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:08:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:08:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:08:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:08:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:08:47 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 18:08:47 - INFO - trainer -     loss = 1.126309831227575\n","09/11/2024 18:08:47 - INFO - trainer -     mean_intent_slot = 0.8732216381148445\n","09/11/2024 18:08:47 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 18:08:47 - INFO - trainer -     slot_f1 = 0.9428718476582604\n","09/11/2024 18:08:47 - INFO - trainer -     slot_precision = 0.9318413021363174\n","09/11/2024 18:08:47 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.82it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:17<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:09:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:09:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:09:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 18:09:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:09:07 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 18:09:07 - INFO - trainer -     loss = 1.0083868381168162\n","09/11/2024 18:09:07 - INFO - trainer -     mean_intent_slot = 0.8806531872008062\n","09/11/2024 18:09:07 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:09:07 - INFO - trainer -     slot_f1 = 0.9475308641975307\n","09/11/2024 18:09:07 - INFO - trainer -     slot_precision = 0.9359756097560976\n","09/11/2024 18:09:07 - INFO - trainer -     slot_recall = 0.959375\n","mean_intent_slot increased (0.879089 --> 0.880653).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.53it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:09:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:09:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:09:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:09:29 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:09:29 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 18:09:29 - INFO - trainer -     loss = 1.0225252378731966\n","09/11/2024 18:09:29 - INFO - trainer -     mean_intent_slot = 0.8770898189784389\n","09/11/2024 18:09:29 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 18:09:29 - INFO - trainer -     slot_f1 = 0.9378531073446328\n","09/11/2024 18:09:29 - INFO - trainer -     slot_precision = 0.9250253292806484\n","09/11/2024 18:09:29 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.85it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:17<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:09:47 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:09:47 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:09:47 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.50it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.54it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.63it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.13it/s]\n","09/11/2024 18:09:49 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:09:49 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 18:09:49 - INFO - trainer -     loss = 0.9587180770135352\n","09/11/2024 18:09:49 - INFO - trainer -     mean_intent_slot = 0.8825780312124849\n","09/11/2024 18:09:49 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 18:09:49 - INFO - trainer -     slot_f1 = 0.9411764705882352\n","09/11/2024 18:09:49 - INFO - trainer -     slot_precision = 0.9325153374233128\n","09/11/2024 18:09:49 - INFO - trainer -     slot_recall = 0.95\n","mean_intent_slot increased (0.880653 --> 0.882578).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.32it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:18<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:10:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:10:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:10:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.05it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:10:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:10:13 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:10:13 - INFO - trainer -     loss = 0.9959303350853068\n","09/11/2024 18:10:13 - INFO - trainer -     mean_intent_slot = 0.8763828453425768\n","09/11/2024 18:10:13 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 18:10:13 - INFO - trainer -     slot_f1 = 0.9313371192565824\n","09/11/2024 18:10:13 - INFO - trainer -     slot_precision = 0.9232343909928352\n","09/11/2024 18:10:13 - INFO - trainer -     slot_recall = 0.9395833333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:17<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:10:32 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:10:32 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:10:32 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.93it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:10:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:10:33 - INFO - trainer -     intent_acc = 0.8112244897959183\n","09/11/2024 18:10:33 - INFO - trainer -     loss = 1.0229494819151503\n","09/11/2024 18:10:33 - INFO - trainer -     mean_intent_slot = 0.8746342623070734\n","09/11/2024 18:10:33 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 18:10:33 - INFO - trainer -     slot_f1 = 0.9380440348182285\n","09/11/2024 18:10:33 - INFO - trainer -     slot_precision = 0.9224572004028198\n","09/11/2024 18:10:33 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:17<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:10:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:10:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:10:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 18:10:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:10:53 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 18:10:53 - INFO - trainer -     loss = 0.9911265814942973\n","09/11/2024 18:10:53 - INFO - trainer -     mean_intent_slot = 0.8792391762906713\n","09/11/2024 18:10:53 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:10:53 - INFO - trainer -     slot_f1 = 0.9447028423772609\n","09/11/2024 18:10:53 - INFO - trainer -     slot_precision = 0.9374358974358974\n","09/11/2024 18:10:53 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.86it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:17<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:11:11 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:11:11 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:11:11 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 18:11:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:11:12 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:11:12 - INFO - trainer -     loss = 1.0140108804085426\n","09/11/2024 18:11:12 - INFO - trainer -     mean_intent_slot = 0.8819888011643857\n","09/11/2024 18:11:12 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:11:12 - INFO - trainer -     slot_f1 = 0.9451000513083633\n","09/11/2024 18:11:12 - INFO - trainer -     slot_precision = 0.9312436804853387\n","09/11/2024 18:11:12 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:17<00:00,  3.17it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:11:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:11:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:11:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.04it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:11:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:11:32 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 18:11:32 - INFO - trainer -     loss = 1.0841915775090456\n","09/11/2024 18:11:32 - INFO - trainer -     mean_intent_slot = 0.8741313729792992\n","09/11/2024 18:11:32 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 18:11:32 - INFO - trainer -     slot_f1 = 0.9421402969790067\n","09/11/2024 18:11:32 - INFO - trainer -     slot_precision = 0.9264853977844915\n","09/11/2024 18:11:32 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.86it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:17<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:11:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:11:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:11:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.66it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.61it/s]\n","09/11/2024 18:11:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:11:52 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:11:52 - INFO - trainer -     loss = 0.9640645159940634\n","09/11/2024 18:11:52 - INFO - trainer -     mean_intent_slot = 0.8980573501848148\n","09/11/2024 18:11:52 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 18:11:52 - INFO - trainer -     slot_f1 = 0.944073884043099\n","09/11/2024 18:11:52 - INFO - trainer -     slot_precision = 0.9302325581395349\n","09/11/2024 18:11:52 - INFO - trainer -     slot_recall = 0.9583333333333334\n","mean_intent_slot increased (0.882578 --> 0.898057).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.33it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:17<00:00,  3.12it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:12:14 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:12:14 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:12:14 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.33it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.56it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.12it/s]\n","09/11/2024 18:12:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:12:16 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:12:16 - INFO - trainer -     loss = 0.9770553378787424\n","09/11/2024 18:12:16 - INFO - trainer -     mean_intent_slot = 0.8937897030580588\n","09/11/2024 18:12:16 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 18:12:16 - INFO - trainer -     slot_f1 = 0.9482936918304032\n","09/11/2024 18:12:16 - INFO - trainer -     slot_precision = 0.9414784394250514\n","09/11/2024 18:12:16 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.82it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:17<00:00,  3.11it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:12:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:12:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:12:34 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:12:36 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:12:36 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:12:36 - INFO - trainer -     loss = 1.028036042914859\n","09/11/2024 18:12:36 - INFO - trainer -     mean_intent_slot = 0.8803899323225435\n","09/11/2024 18:12:36 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 18:12:36 - INFO - trainer -     slot_f1 = 0.9419023136246787\n","09/11/2024 18:12:36 - INFO - trainer -     slot_precision = 0.9299492385786802\n","09/11/2024 18:12:36 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.82it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:17<00:00,  3.14it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:12:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:12:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:12:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.66it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.73it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.15it/s]\n","09/11/2024 18:12:56 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:12:56 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 18:12:56 - INFO - trainer -     loss = 0.9914689240977168\n","09/11/2024 18:12:56 - INFO - trainer -     mean_intent_slot = 0.8942594849318508\n","09/11/2024 18:12:56 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 18:12:56 - INFO - trainer -     slot_f1 = 0.9441312147616607\n","09/11/2024 18:12:56 - INFO - trainer -     slot_precision = 0.929364278506559\n","09/11/2024 18:12:56 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:17<00:00,  3.10it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:13:14 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:13:14 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:13:14 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.04it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.75it/s]\n","09/11/2024 18:13:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:13:15 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:13:15 - INFO - trainer -     loss = 0.9960378178927515\n","09/11/2024 18:13:15 - INFO - trainer -     mean_intent_slot = 0.8952931582469054\n","09/11/2024 18:13:15 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 18:13:15 - INFO - trainer -     slot_f1 = 0.9436475409836066\n","09/11/2024 18:13:15 - INFO - trainer -     slot_precision = 0.9284274193548387\n","09/11/2024 18:13:15 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:17<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:13:33 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:13:33 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:13:33 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.71it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.22it/s]\n","09/11/2024 18:13:35 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:13:35 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 18:13:35 - INFO - trainer -     loss = 1.01909506706787\n","09/11/2024 18:13:35 - INFO - trainer -     mean_intent_slot = 0.8919435398582214\n","09/11/2024 18:13:35 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 18:13:35 - INFO - trainer -     slot_f1 = 0.9471523858388917\n","09/11/2024 18:13:35 - INFO - trainer -     slot_precision = 0.9332659251769464\n","09/11/2024 18:13:35 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:13:53 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:13:53 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:13:53 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.75it/s]\n","09/11/2024 18:13:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:13:55 - INFO - trainer -     intent_acc = 0.8290816326530612\n","09/11/2024 18:13:55 - INFO - trainer -     loss = 1.0436864206567407\n","09/11/2024 18:13:55 - INFO - trainer -     mean_intent_slot = 0.8879807338097694\n","09/11/2024 18:13:55 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 18:13:55 - INFO - trainer -     slot_f1 = 0.9468798349664777\n","09/11/2024 18:13:55 - INFO - trainer -     slot_precision = 0.9376915219611849\n","09/11/2024 18:13:55 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:17<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:14:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:14:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:14:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.78it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.30it/s]\n","09/11/2024 18:14:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:14:15 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:14:15 - INFO - trainer -     loss = 1.0679663860106043\n","09/11/2024 18:14:15 - INFO - trainer -     mean_intent_slot = 0.881242220106905\n","09/11/2024 18:14:15 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 18:14:15 - INFO - trainer -     slot_f1 = 0.9410558687852385\n","09/11/2024 18:14:15 - INFO - trainer -     slot_precision = 0.9263370332996973\n","09/11/2024 18:14:15 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:19<00:00,  2.55it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:14:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:14:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:14:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.02it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 18:14:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:14:37 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:14:37 - INFO - trainer -     loss = 1.0603054108630334\n","09/11/2024 18:14:37 - INFO - trainer -     mean_intent_slot = 0.8884326760386856\n","09/11/2024 18:14:37 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 18:14:37 - INFO - trainer -     slot_f1 = 0.9426816786079836\n","09/11/2024 18:14:37 - INFO - trainer -     slot_precision = 0.9265593561368209\n","09/11/2024 18:14:37 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:21<00:00,  2.55it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:17<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:14:55 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:14:55 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:14:55 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.70it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.59it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.05it/s]\n","09/11/2024 18:14:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:14:57 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:14:57 - INFO - trainer -     loss = 1.0710623945508684\n","09/11/2024 18:14:57 - INFO - trainer -     mean_intent_slot = 0.8821250169286704\n","09/11/2024 18:14:57 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 18:14:57 - INFO - trainer -     slot_f1 = 0.9300663603879531\n","09/11/2024 18:14:57 - INFO - trainer -     slot_precision = 0.9119119119119119\n","09/11/2024 18:14:57 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:15:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:15:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:15:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:15:17 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:15:17 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 18:15:17 - INFO - trainer -     loss = 2.5461963606732234\n","09/11/2024 18:15:17 - INFO - trainer -     mean_intent_slot = 0.6649907277145416\n","09/11/2024 18:15:17 - INFO - trainer -     semantic_frame_acc = 0.11734693877551021\n","09/11/2024 18:15:17 - INFO - trainer -     slot_f1 = 0.5264100268576546\n","09/11/2024 18:15:17 - INFO - trainer -     slot_precision = 0.46153846153846156\n","09/11/2024 18:15:17 - INFO - trainer -     slot_recall = 0.6125\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:17<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:15:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:15:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:15:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.48it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.50it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.53it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.57it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.58it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.01it/s]\n","09/11/2024 18:15:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:15:37 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:15:37 - INFO - trainer -     loss = 1.0673616692157728\n","09/11/2024 18:15:37 - INFO - trainer -     mean_intent_slot = 0.8819888011643857\n","09/11/2024 18:15:37 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 18:15:37 - INFO - trainer -     slot_f1 = 0.9451000513083633\n","09/11/2024 18:15:37 - INFO - trainer -     slot_precision = 0.9312436804853387\n","09/11/2024 18:15:37 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:15:56 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:15:56 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:15:56 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.13it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:15:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:15:57 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 18:15:57 - INFO - trainer -     loss = 1.1070082980607237\n","09/11/2024 18:15:57 - INFO - trainer -     mean_intent_slot = 0.8779129276133234\n","09/11/2024 18:15:57 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 18:15:57 - INFO - trainer -     slot_f1 = 0.9471523858388917\n","09/11/2024 18:15:57 - INFO - trainer -     slot_precision = 0.9332659251769464\n","09/11/2024 18:15:57 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:17<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:16:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:16:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:16:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.51it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.57it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.63it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.62it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.57it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.07it/s]\n","09/11/2024 18:16:17 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:16:17 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:16:17 - INFO - trainer -     loss = 1.0792421192329908\n","09/11/2024 18:16:17 - INFO - trainer -     mean_intent_slot = 0.8833205325140809\n","09/11/2024 18:16:17 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 18:16:17 - INFO - trainer -     slot_f1 = 0.9452124935995904\n","09/11/2024 18:16:17 - INFO - trainer -     slot_precision = 0.9295065458207452\n","09/11/2024 18:16:17 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:16:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:16:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:16:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.66it/s]\n","09/11/2024 18:16:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:16:37 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:16:37 - INFO - trainer -     loss = 1.0318595099795078\n","09/11/2024 18:16:37 - INFO - trainer -     mean_intent_slot = 0.8958054533288726\n","09/11/2024 18:16:37 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 18:16:37 - INFO - trainer -     slot_f1 = 0.944672131147541\n","09/11/2024 18:16:37 - INFO - trainer -     slot_precision = 0.9294354838709677\n","09/11/2024 18:16:37 - INFO - trainer -     slot_recall = 0.9604166666666667\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.85it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:17<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:16:55 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:16:55 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:16:55 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.17it/s]\n","09/11/2024 18:16:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:16:57 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:16:57 - INFO - trainer -     loss = 1.0482793050552053\n","09/11/2024 18:16:57 - INFO - trainer -     mean_intent_slot = 0.8932827481043595\n","09/11/2024 18:16:57 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 18:16:57 - INFO - trainer -     slot_f1 = 0.9447287615148414\n","09/11/2024 18:16:57 - INFO - trainer -     slot_precision = 0.9285714285714286\n","09/11/2024 18:16:57 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:17<00:00,  3.14it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:17:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:17:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:17:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:17:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:17:16 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:17:16 - INFO - trainer -     loss = 1.034862145781517\n","09/11/2024 18:17:16 - INFO - trainer -     mean_intent_slot = 0.8981146221929632\n","09/11/2024 18:17:16 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 18:17:16 - INFO - trainer -     slot_f1 = 0.9441884280593958\n","09/11/2024 18:17:16 - INFO - trainer -     slot_precision = 0.9284994964753273\n","09/11/2024 18:17:16 - INFO - trainer -     slot_recall = 0.9604166666666667\n","mean_intent_slot increased (0.898057 --> 0.898115).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.26it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:17<00:00,  3.13it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:17:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:17:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:17:39 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.05it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:17:41 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:17:41 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:17:41 - INFO - trainer -     loss = 1.0437598446650165\n","09/11/2024 18:17:41 - INFO - trainer -     mean_intent_slot = 0.8982996689435527\n","09/11/2024 18:17:41 - INFO - trainer -     semantic_frame_acc = 0.7142857142857143\n","09/11/2024 18:17:41 - INFO - trainer -     slot_f1 = 0.944558521560575\n","09/11/2024 18:17:41 - INFO - trainer -     slot_precision = 0.9311740890688259\n","09/11/2024 18:17:41 - INFO - trainer -     slot_recall = 0.9583333333333334\n","mean_intent_slot increased (0.898115 --> 0.898300).  Saving model ...\n","Iteration: 100% 56/56 [00:21<00:00,  2.55it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:17<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:18:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:18:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:18:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.62it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.55it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.55it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.58it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.01it/s]\n","09/11/2024 18:18:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:18:03 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:18:03 - INFO - trainer -     loss = 1.0556080542238695\n","09/11/2024 18:18:03 - INFO - trainer -     mean_intent_slot = 0.8995694579835015\n","09/11/2024 18:18:03 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 18:18:03 - INFO - trainer -     slot_f1 = 0.9470980996404724\n","09/11/2024 18:18:03 - INFO - trainer -     slot_precision = 0.9341438703140831\n","09/11/2024 18:18:03 - INFO - trainer -     slot_recall = 0.9604166666666667\n","mean_intent_slot increased (0.898300 --> 0.899569).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.20it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:17<00:00,  3.18it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:18:27 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:18:27 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:18:27 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.41it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.58it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.70it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.76it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.83it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.25it/s]\n","09/11/2024 18:18:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:18:28 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:18:28 - INFO - trainer -     loss = 1.0654594807752542\n","09/11/2024 18:18:28 - INFO - trainer -     mean_intent_slot = 0.8967204165616864\n","09/11/2024 18:18:28 - INFO - trainer -     semantic_frame_acc = 0.7193877551020408\n","09/11/2024 18:18:28 - INFO - trainer -     slot_f1 = 0.9465020576131687\n","09/11/2024 18:18:28 - INFO - trainer -     slot_precision = 0.9349593495934959\n","09/11/2024 18:18:28 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:17<00:00,  3.17it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:18:47 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:18:47 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:18:47 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.94it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:18:48 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:18:48 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:18:48 - INFO - trainer -     loss = 1.0740434434930128\n","09/11/2024 18:18:48 - INFO - trainer -     mean_intent_slot = 0.8922592066509305\n","09/11/2024 18:18:48 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:18:48 - INFO - trainer -     slot_f1 = 0.9426816786079836\n","09/11/2024 18:18:48 - INFO - trainer -     slot_precision = 0.9265593561368209\n","09/11/2024 18:18:48 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.86it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:17<00:00,  3.17it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:19:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:19:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:19:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.26it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.60it/s]\n","09/11/2024 18:19:08 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:19:08 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 18:19:08 - INFO - trainer -     loss = 1.081225745978632\n","09/11/2024 18:19:08 - INFO - trainer -     mean_intent_slot = 0.8945015698587127\n","09/11/2024 18:19:08 - INFO - trainer -     semantic_frame_acc = 0.701530612244898\n","09/11/2024 18:19:08 - INFO - trainer -     slot_f1 = 0.9446153846153845\n","09/11/2024 18:19:08 - INFO - trainer -     slot_precision = 0.9303030303030303\n","09/11/2024 18:19:08 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.86it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:17<00:00,  3.11it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:19:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:19:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:19:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:19:27 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:19:27 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:19:27 - INFO - trainer -     loss = 1.0759004970480288\n","09/11/2024 18:19:27 - INFO - trainer -     mean_intent_slot = 0.8957770800627943\n","09/11/2024 18:19:27 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 18:19:27 - INFO - trainer -     slot_f1 = 0.9446153846153845\n","09/11/2024 18:19:27 - INFO - trainer -     slot_precision = 0.9303030303030303\n","09/11/2024 18:19:27 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.84it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:17<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:19:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:19:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:19:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:19:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:19:47 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 18:19:47 - INFO - trainer -     loss = 1.1003495447470673\n","09/11/2024 18:19:47 - INFO - trainer -     mean_intent_slot = 0.8906750392464677\n","09/11/2024 18:19:47 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:19:47 - INFO - trainer -     slot_f1 = 0.9446153846153845\n","09/11/2024 18:19:47 - INFO - trainer -     slot_precision = 0.9303030303030303\n","09/11/2024 18:19:47 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.87it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:17<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:20:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:20:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:20:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.09it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 18:20:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:20:07 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:20:07 - INFO - trainer -     loss = 1.1083566207172615\n","09/11/2024 18:20:07 - INFO - trainer -     mean_intent_slot = 0.8881026114909791\n","09/11/2024 18:20:07 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 18:20:07 - INFO - trainer -     slot_f1 = 0.9420215495125706\n","09/11/2024 18:20:07 - INFO - trainer -     slot_precision = 0.9282103134479271\n","09/11/2024 18:20:07 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:17<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:20:25 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:20:25 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:20:25 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:20:26 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:20:26 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:20:26 - INFO - trainer -     loss = 1.1179078851959534\n","09/11/2024 18:20:26 - INFO - trainer -     mean_intent_slot = 0.8871278019404483\n","09/11/2024 18:20:26 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:20:26 - INFO - trainer -     slot_f1 = 0.9426229508196722\n","09/11/2024 18:20:26 - INFO - trainer -     slot_precision = 0.9274193548387096\n","09/11/2024 18:20:26 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:17<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:20:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:20:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:20:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:20:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:20:46 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:20:46 - INFO - trainer -     loss = 1.1155048907468361\n","09/11/2024 18:20:46 - INFO - trainer -     mean_intent_slot = 0.8866155068584811\n","09/11/2024 18:20:46 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 18:20:46 - INFO - trainer -     slot_f1 = 0.9415983606557377\n","09/11/2024 18:20:46 - INFO - trainer -     slot_precision = 0.9264112903225806\n","09/11/2024 18:20:46 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.83it/s]\n","Epoch: 100% 50/50 [17:33<00:00, 21.07s/it]\n","09/11/2024 18:20:46 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 18:20:46 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 18:20:46 - INFO - trainer -     Num examples = 346\n","09/11/2024 18:20:46 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.62it/s]\n","09/11/2024 18:20:48 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:20:48 - INFO - trainer -     intent_acc = 0.8583815028901735\n","09/11/2024 18:20:48 - INFO - trainer -     loss = 1.131277158856392\n","09/11/2024 18:20:48 - INFO - trainer -     mean_intent_slot = 0.8974245506826979\n","09/11/2024 18:20:48 - INFO - trainer -     semantic_frame_acc = 0.6878612716763006\n","09/11/2024 18:20:48 - INFO - trainer -     slot_f1 = 0.9364675984752224\n","09/11/2024 18:20:48 - INFO - trainer -     slot_precision = 0.92125\n","09/11/2024 18:20:48 - INFO - trainer -     slot_recall = 0.9521963824289406\n"]}]},{"cell_type":"code","source":["# First, run the previous bash script to train JointBERT-CRF_PhoBERTencoder\n","# !bash run_jointBERT-CRF_PhoBERTencoder.sh\n","\n","# Now set up environment variables for the new training run\n","lr = \"4e-5\"\n","c = \"0.5\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Set the MODEL_DIR path for JointIDSF\n","MODEL_DIR = f\"Model_Hackathon/JointIDSF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Run the second python script using the pretrained model path\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_intent_context_attention \\\n","                  --attention_embedding_size 200 \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --pretrained \\\n","                  --pretrained_path Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2eSPB_eyvIoo","executionInfo":{"status":"ok","timestamp":1726080028141,"user_tz":-420,"elapsed":1086320,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"d238bd2e-1c67-4b3f-94b4-0f04c9e9c83d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["4e-5\n","Model_Hackathon/JointIDSF_CLPhoBERTencoder/4e-5/0.5/100\n","2024-09-11 18:22:35.391451: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 18:22:35.412078: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 18:22:35.418602: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 18:22:35.434178: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 18:22:36.785371: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","09/11/2024 18:22:38 - INFO - data_loader -   Loading features from cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","/content/ViNLU/data_loader.py:238: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n","  features = torch.load(cached_features_file)\n","09/11/2024 18:22:38 - INFO - data_loader -   Loading features from cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 18:22:38 - INFO - data_loader -   Loading features from cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","phongtintruong/clphobert-base-16-256-50-30\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 and are newly initialized: ['slot_classifier.attention.linear_out.weight', 'slot_classifier.linear_intent_context.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 18:22:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:22:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:22:39 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:02<00:00,  2.48it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 18:22:42 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:22:42 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:22:42 - INFO - trainer -     loss = 19.67234516143799\n","09/11/2024 18:22:42 - INFO - trainer -     mean_intent_slot = 0.4339380645369787\n","09/11/2024 18:22:42 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 18:22:42 - INFO - trainer -     slot_f1 = 0.015835312747426764\n","09/11/2024 18:22:42 - INFO - trainer -     slot_precision = 0.010604453870625663\n","09/11/2024 18:22:42 - INFO - trainer -     slot_recall = 0.03125\n","{'loss': 19.67234516143799, 'intent_acc': 0.8520408163265306, 'slot_precision': 0.010604453870625663, 'slot_recall': 0.03125, 'slot_f1': 0.015835312747426764, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.4339380645369787}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 18:22:42 - INFO - trainer -   ***** Running training *****\n","09/11/2024 18:22:42 - INFO - trainer -     Num examples = 1790\n","09/11/2024 18:22:42 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 18:22:42 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 18:22:42 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 18:22:42 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 18:22:42 - INFO - trainer -     Logging steps = 56\n","09/11/2024 18:22:42 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:16<00:00,  3.26it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:22:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:22:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:22:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.53it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.60it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.57it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.56it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.52it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.08it/s]\n","09/11/2024 18:23:01 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:23:01 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:23:01 - INFO - trainer -     loss = 6.775158711842129\n","09/11/2024 18:23:01 - INFO - trainer -     mean_intent_slot = 0.8485861158622741\n","09/11/2024 18:23:01 - INFO - trainer -     semantic_frame_acc = 0.3137755102040816\n","09/11/2024 18:23:01 - INFO - trainer -     slot_f1 = 0.8578865174388338\n","09/11/2024 18:23:01 - INFO - trainer -     slot_precision = 0.8574401664932362\n","09/11/2024 18:23:01 - INFO - trainer -     slot_recall = 0.8583333333333333\n","mean_intent_slot increased (inf --> 0.848586).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.50it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:17<00:00,  3.20it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:23:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:23:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:23:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.36it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.46it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.50it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.52it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.48it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.03it/s]\n","09/11/2024 18:23:24 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:23:24 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 18:23:24 - INFO - trainer -     loss = 3.1731237173080444\n","09/11/2024 18:23:24 - INFO - trainer -     mean_intent_slot = 0.8676020408163265\n","09/11/2024 18:23:24 - INFO - trainer -     semantic_frame_acc = 0.5994897959183674\n","09/11/2024 18:23:24 - INFO - trainer -     slot_f1 = 0.9112244897959183\n","09/11/2024 18:23:24 - INFO - trainer -     slot_precision = 0.893\n","09/11/2024 18:23:24 - INFO - trainer -     slot_recall = 0.9302083333333333\n","mean_intent_slot increased (0.848586 --> 0.867602).  Saving model ...\n","Iteration: 100% 56/56 [00:21<00:00,  2.55it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:17<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:23:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:23:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:23:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.86it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.77it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.26it/s]\n","09/11/2024 18:23:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:23:46 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:23:46 - INFO - trainer -     loss = 2.0706355614321574\n","09/11/2024 18:23:46 - INFO - trainer -     mean_intent_slot = 0.8776114495721875\n","09/11/2024 18:23:46 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 18:23:46 - INFO - trainer -     slot_f1 = 0.9210392256749873\n","09/11/2024 18:23:46 - INFO - trainer -     slot_precision = 0.901296111665005\n","09/11/2024 18:23:46 - INFO - trainer -     slot_recall = 0.9416666666666667\n","mean_intent_slot increased (0.867602 --> 0.877611).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.51it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:24:07 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:24:07 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:24:07 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.75it/s]\n","09/11/2024 18:24:09 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:24:09 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:24:09 - INFO - trainer -     loss = 1.6518542000225611\n","09/11/2024 18:24:09 - INFO - trainer -     mean_intent_slot = 0.8776974119550033\n","09/11/2024 18:24:09 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 18:24:09 - INFO - trainer -     slot_f1 = 0.9161091096242923\n","09/11/2024 18:24:09 - INFO - trainer -     slot_precision = 0.9053916581892166\n","09/11/2024 18:24:09 - INFO - trainer -     slot_recall = 0.9270833333333334\n","mean_intent_slot increased (0.877611 --> 0.877697).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.48it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:24:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:24:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:24:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.27it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.78it/s]\n","09/11/2024 18:24:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:24:32 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:24:32 - INFO - trainer -     loss = 1.5150165376918656\n","09/11/2024 18:24:32 - INFO - trainer -     mean_intent_slot = 0.8732512117997046\n","09/11/2024 18:24:32 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 18:24:32 - INFO - trainer -     slot_f1 = 0.927624872579001\n","09/11/2024 18:24:32 - INFO - trainer -     slot_precision = 0.908183632734531\n","09/11/2024 18:24:32 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:18<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:24:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:24:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:24:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.89it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.88it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.41it/s]\n","09/11/2024 18:24:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:24:52 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 18:24:52 - INFO - trainer -     loss = 1.1977505428450448\n","09/11/2024 18:24:52 - INFO - trainer -     mean_intent_slot = 0.8890463592844546\n","09/11/2024 18:24:52 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 18:24:52 - INFO - trainer -     slot_f1 = 0.9413580246913581\n","09/11/2024 18:24:52 - INFO - trainer -     slot_precision = 0.9298780487804879\n","09/11/2024 18:24:52 - INFO - trainer -     slot_recall = 0.953125\n","mean_intent_slot increased (0.877697 --> 0.889046).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.44it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:25:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:25:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:25:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.77it/s]\n","09/11/2024 18:25:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:25:15 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:25:15 - INFO - trainer -     loss = 1.3020008568252837\n","09/11/2024 18:25:15 - INFO - trainer -     mean_intent_slot = 0.8897159320349144\n","09/11/2024 18:25:15 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:25:15 - INFO - trainer -     slot_f1 = 0.9375951293759514\n","09/11/2024 18:25:15 - INFO - trainer -     slot_precision = 0.913946587537092\n","09/11/2024 18:25:15 - INFO - trainer -     slot_recall = 0.9625\n","mean_intent_slot increased (0.889046 --> 0.889716).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.52it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:25:36 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:25:36 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:25:36 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:25:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:25:37 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:25:37 - INFO - trainer -     loss = 1.1823464701218265\n","09/11/2024 18:25:37 - INFO - trainer -     mean_intent_slot = 0.8836105169997788\n","09/11/2024 18:25:37 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 18:25:37 - INFO - trainer -     slot_f1 = 0.9457924625709861\n","09/11/2024 18:25:37 - INFO - trainer -     slot_precision = 0.9375639713408394\n","09/11/2024 18:25:37 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:25:56 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:25:56 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:25:56 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.23it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:25:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:25:57 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 18:25:57 - INFO - trainer -     loss = 1.3161328711680003\n","09/11/2024 18:25:57 - INFO - trainer -     mean_intent_slot = 0.8797361157577785\n","09/11/2024 18:25:57 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:25:57 - INFO - trainer -     slot_f1 = 0.9456967213114754\n","09/11/2024 18:25:57 - INFO - trainer -     slot_precision = 0.9304435483870968\n","09/11/2024 18:25:57 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:26:16 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:26:16 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:26:16 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.24it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.16it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 18:26:18 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:26:18 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:26:18 - INFO - trainer -     loss = 1.2661282257842166\n","09/11/2024 18:26:18 - INFO - trainer -     mean_intent_slot = 0.8871044796604622\n","09/11/2024 18:26:18 - INFO - trainer -     semantic_frame_acc = 0.7117346938775511\n","09/11/2024 18:26:18 - INFO - trainer -     slot_f1 = 0.9425763062597\n","09/11/2024 18:26:18 - INFO - trainer -     slot_precision = 0.9362795477903392\n","09/11/2024 18:26:18 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:26:37 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:26:37 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:26:37 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.04it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.55it/s]\n","09/11/2024 18:26:38 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:26:38 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 18:26:38 - INFO - trainer -     loss = 1.2196114111159528\n","09/11/2024 18:26:38 - INFO - trainer -     mean_intent_slot = 0.8930825394509182\n","09/11/2024 18:26:38 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 18:26:38 - INFO - trainer -     slot_f1 = 0.9417773237997956\n","09/11/2024 18:26:38 - INFO - trainer -     slot_precision = 0.9238476953907816\n","09/11/2024 18:26:38 - INFO - trainer -     slot_recall = 0.9604166666666667\n","mean_intent_slot increased (0.889716 --> 0.893083).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.43it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:27:00 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:27:00 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:27:00 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:27:01 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:27:01 - INFO - trainer -     intent_acc = 0.8290816326530612\n","09/11/2024 18:27:01 - INFO - trainer -     loss = 1.3343229150133473\n","09/11/2024 18:27:01 - INFO - trainer -     mean_intent_slot = 0.884315406490465\n","09/11/2024 18:27:01 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:27:01 - INFO - trainer -     slot_f1 = 0.9395491803278689\n","09/11/2024 18:27:01 - INFO - trainer -     slot_precision = 0.9243951612903226\n","09/11/2024 18:27:01 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:18<00:00,  2.78it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:27:20 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:27:20 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:27:20 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.56it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.58it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.98it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.06it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.47it/s]\n","09/11/2024 18:27:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:27:22 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:27:22 - INFO - trainer -     loss = 1.2226322719029017\n","09/11/2024 18:27:22 - INFO - trainer -     mean_intent_slot = 0.8887940150153326\n","09/11/2024 18:27:22 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 18:27:22 - INFO - trainer -     slot_f1 = 0.9357512953367876\n","09/11/2024 18:27:22 - INFO - trainer -     slot_precision = 0.9309278350515464\n","09/11/2024 18:27:22 - INFO - trainer -     slot_recall = 0.940625\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:27:41 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:27:41 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:27:41 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.08it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 18:27:42 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:27:42 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:27:42 - INFO - trainer -     loss = 1.3674334061465092\n","09/11/2024 18:27:42 - INFO - trainer -     mean_intent_slot = 0.8890019490942445\n","09/11/2024 18:27:42 - INFO - trainer -     semantic_frame_acc = 0.701530612244898\n","09/11/2024 18:27:42 - INFO - trainer -     slot_f1 = 0.9438202247191011\n","09/11/2024 18:27:42 - INFO - trainer -     slot_precision = 0.9258517034068137\n","09/11/2024 18:27:42 - INFO - trainer -     slot_recall = 0.9625\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:18<00:00,  2.83it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:28:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:28:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:28:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.72it/s]\n","09/11/2024 18:28:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:28:03 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 18:28:03 - INFO - trainer -     loss = 1.4124142955988646\n","09/11/2024 18:28:03 - INFO - trainer -     mean_intent_slot = 0.8754696824578206\n","09/11/2024 18:28:03 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:28:03 - INFO - trainer -     slot_f1 = 0.9448169159360494\n","09/11/2024 18:28:03 - INFO - trainer -     slot_precision = 0.9356486210418795\n","09/11/2024 18:28:03 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:28:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:28:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:28:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:28:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:28:23 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 18:28:23 - INFO - trainer -     loss = 1.316550544330052\n","09/11/2024 18:28:23 - INFO - trainer -     mean_intent_slot = 0.8851580105726502\n","09/11/2024 18:28:23 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 18:28:23 - INFO - trainer -     slot_f1 = 0.9463364293085657\n","09/11/2024 18:28:23 - INFO - trainer -     slot_precision = 0.9376278118609407\n","09/11/2024 18:28:23 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:18<00:00,  2.84it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:28:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:28:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:28:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.97it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.69it/s]\n","09/11/2024 18:28:44 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:28:44 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:28:44 - INFO - trainer -     loss = 1.343702846738909\n","09/11/2024 18:28:44 - INFO - trainer -     mean_intent_slot = 0.8868568185859684\n","09/11/2024 18:28:44 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 18:28:44 - INFO - trainer -     slot_f1 = 0.9420809841107124\n","09/11/2024 18:28:44 - INFO - trainer -     slot_precision = 0.9273461150353178\n","09/11/2024 18:28:44 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.71it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:29:03 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:29:03 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:29:03 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:29:05 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:29:05 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:29:05 - INFO - trainer -     loss = 1.301766005411212\n","09/11/2024 18:29:05 - INFO - trainer -     mean_intent_slot = 0.8908031769408794\n","09/11/2024 18:29:05 - INFO - trainer -     semantic_frame_acc = 0.7168367346938775\n","09/11/2024 18:29:05 - INFO - trainer -     slot_f1 = 0.9474226804123711\n","09/11/2024 18:29:05 - INFO - trainer -     slot_precision = 0.9377551020408164\n","09/11/2024 18:29:05 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:19<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:29:24 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:29:24 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:29:24 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.04it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.63it/s]\n","09/11/2024 18:29:26 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:29:26 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:29:26 - INFO - trainer -     loss = 1.2473710806641196\n","09/11/2024 18:29:26 - INFO - trainer -     mean_intent_slot = 0.892866338090334\n","09/11/2024 18:29:26 - INFO - trainer -     semantic_frame_acc = 0.7244897959183674\n","09/11/2024 18:29:26 - INFO - trainer -     slot_f1 = 0.9464469618949537\n","09/11/2024 18:29:26 - INFO - trainer -     slot_precision = 0.9358452138492872\n","09/11/2024 18:29:26 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:21<00:00,  2.65it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:29:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:29:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:29:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.07it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.08it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.89it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.37it/s]\n","09/11/2024 18:29:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:29:46 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:29:46 - INFO - trainer -     loss = 1.2445533209746438\n","09/11/2024 18:29:46 - INFO - trainer -     mean_intent_slot = 0.8935705861291885\n","09/11/2024 18:29:46 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 18:29:46 - INFO - trainer -     slot_f1 = 0.9453044375644994\n","09/11/2024 18:29:46 - INFO - trainer -     slot_precision = 0.9366053169734151\n","09/11/2024 18:29:46 - INFO - trainer -     slot_recall = 0.9541666666666667\n","mean_intent_slot increased (0.893083 --> 0.893571).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.39it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:30:08 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:30:08 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:30:08 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.58it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.05it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.60it/s]\n","09/11/2024 18:30:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:30:10 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:30:10 - INFO - trainer -     loss = 1.3857784093623715\n","09/11/2024 18:30:10 - INFO - trainer -     mean_intent_slot = 0.8915327500443202\n","09/11/2024 18:30:10 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 18:30:10 - INFO - trainer -     slot_f1 = 0.9361267245784364\n","09/11/2024 18:30:10 - INFO - trainer -     slot_precision = 0.9187562688064193\n","09/11/2024 18:30:10 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:18<00:00,  2.79it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:30:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:30:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:30:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.41it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.41it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.86it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.96it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.36it/s]\n","09/11/2024 18:30:31 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:30:31 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:30:31 - INFO - trainer -     loss = 1.4034525798633695\n","09/11/2024 18:30:31 - INFO - trainer -     mean_intent_slot = 0.8913357116625571\n","09/11/2024 18:30:31 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 18:30:31 - INFO - trainer -     slot_f1 = 0.93573264781491\n","09/11/2024 18:30:31 - INFO - trainer -     slot_precision = 0.9238578680203046\n","09/11/2024 18:30:31 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.68it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:30:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:30:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:30:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.01it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.13it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.61it/s]\n","09/11/2024 18:30:51 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:30:51 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 18:30:51 - INFO - trainer -     loss = 1.2955132427492313\n","09/11/2024 18:30:51 - INFO - trainer -     mean_intent_slot = 0.8964235797305535\n","09/11/2024 18:30:51 - INFO - trainer -     semantic_frame_acc = 0.7142857142857143\n","09/11/2024 18:30:51 - INFO - trainer -     slot_f1 = 0.9433573635427396\n","09/11/2024 18:30:51 - INFO - trainer -     slot_precision = 0.9327902240325866\n","09/11/2024 18:30:51 - INFO - trainer -     slot_recall = 0.9541666666666667\n","mean_intent_slot increased (0.893571 --> 0.896424).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.43it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:31:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:31:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:31:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.69it/s]\n","09/11/2024 18:31:14 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:31:14 - INFO - trainer -     intent_acc = 0.8545918367346939\n","09/11/2024 18:31:14 - INFO - trainer -     loss = 1.2817767736102854\n","09/11/2024 18:31:14 - INFO - trainer -     mean_intent_slot = 0.8994608668209552\n","09/11/2024 18:31:14 - INFO - trainer -     semantic_frame_acc = 0.7244897959183674\n","09/11/2024 18:31:14 - INFO - trainer -     slot_f1 = 0.9443298969072165\n","09/11/2024 18:31:14 - INFO - trainer -     slot_precision = 0.9346938775510204\n","09/11/2024 18:31:14 - INFO - trainer -     slot_recall = 0.9541666666666667\n","mean_intent_slot increased (0.896424 --> 0.899461).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.16it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:31:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:31:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:31:39 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.16it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:31:40 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:31:40 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 18:31:40 - INFO - trainer -     loss = 1.3108746885055942\n","09/11/2024 18:31:40 - INFO - trainer -     mean_intent_slot = 0.8953634546602146\n","09/11/2024 18:31:40 - INFO - trainer -     semantic_frame_acc = 0.7142857142857143\n","09/11/2024 18:31:40 - INFO - trainer -     slot_f1 = 0.9412371134020618\n","09/11/2024 18:31:40 - INFO - trainer -     slot_precision = 0.9316326530612244\n","09/11/2024 18:31:40 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:31:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:31:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:31:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.08it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.11it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.62it/s]\n","09/11/2024 18:32:01 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:32:01 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:32:01 - INFO - trainer -     loss = 1.2998784104628223\n","09/11/2024 18:32:01 - INFO - trainer -     mean_intent_slot = 0.9009816884936731\n","09/11/2024 18:32:01 - INFO - trainer -     semantic_frame_acc = 0.7321428571428571\n","09/11/2024 18:32:01 - INFO - trainer -     slot_f1 = 0.9499225606608156\n","09/11/2024 18:32:01 - INFO - trainer -     slot_precision = 0.9416581371545547\n","09/11/2024 18:32:01 - INFO - trainer -     slot_recall = 0.9583333333333334\n","mean_intent_slot increased (0.899461 --> 0.900982).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.23it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:32:24 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:32:24 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:32:24 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.02it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.66it/s]\n","09/11/2024 18:32:26 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:32:26 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:32:26 - INFO - trainer -     loss = 1.3023335400835745\n","09/11/2024 18:32:26 - INFO - trainer -     mean_intent_slot = 0.8954160489543577\n","09/11/2024 18:32:26 - INFO - trainer -     semantic_frame_acc = 0.7193877551020408\n","09/11/2024 18:32:26 - INFO - trainer -     slot_f1 = 0.9489953632148377\n","09/11/2024 18:32:26 - INFO - trainer -     slot_precision = 0.9388379204892966\n","09/11/2024 18:32:26 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:32:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:32:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:32:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.09it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.09it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.09it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 18:32:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:32:47 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 18:32:47 - INFO - trainer -     loss = 1.313700117636472\n","09/11/2024 18:32:47 - INFO - trainer -     mean_intent_slot = 0.8971533559272085\n","09/11/2024 18:32:47 - INFO - trainer -     semantic_frame_acc = 0.7168367346938775\n","09/11/2024 18:32:47 - INFO - trainer -     slot_f1 = 0.9448169159360494\n","09/11/2024 18:32:47 - INFO - trainer -     slot_precision = 0.9356486210418795\n","09/11/2024 18:32:47 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:33:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:33:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:33:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.13it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:33:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:33:07 - INFO - trainer -     intent_acc = 0.8545918367346939\n","09/11/2024 18:33:07 - INFO - trainer -     loss = 1.2816613367426075\n","09/11/2024 18:33:07 - INFO - trainer -     mean_intent_slot = 0.9014961247656957\n","09/11/2024 18:33:07 - INFO - trainer -     semantic_frame_acc = 0.7244897959183674\n","09/11/2024 18:33:07 - INFO - trainer -     slot_f1 = 0.9484004127966976\n","09/11/2024 18:33:07 - INFO - trainer -     slot_precision = 0.9396728016359919\n","09/11/2024 18:33:07 - INFO - trainer -     slot_recall = 0.9572916666666667\n","mean_intent_slot increased (0.900982 --> 0.901496).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.42it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:33:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:33:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:33:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.11it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.60it/s]\n","09/11/2024 18:33:30 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:33:30 - INFO - trainer -     intent_acc = 0.8596938775510204\n","09/11/2024 18:33:30 - INFO - trainer -     loss = 1.207521540844547\n","09/11/2024 18:33:30 - INFO - trainer -     mean_intent_slot = 0.9056201346517989\n","09/11/2024 18:33:30 - INFO - trainer -     semantic_frame_acc = 0.7321428571428571\n","09/11/2024 18:33:30 - INFO - trainer -     slot_f1 = 0.9515463917525773\n","09/11/2024 18:33:30 - INFO - trainer -     slot_precision = 0.9418367346938775\n","09/11/2024 18:33:30 - INFO - trainer -     slot_recall = 0.9614583333333333\n","mean_intent_slot increased (0.901496 --> 0.905620).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.43it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:19<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:33:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:33:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:33:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.66it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.65it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.11it/s]\n","09/11/2024 18:33:54 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:33:54 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:33:54 - INFO - trainer -     loss = 1.1982359573178525\n","09/11/2024 18:33:54 - INFO - trainer -     mean_intent_slot = 0.9070799733668713\n","09/11/2024 18:33:54 - INFO - trainer -     semantic_frame_acc = 0.7423469387755102\n","09/11/2024 18:33:54 - INFO - trainer -     slot_f1 = 0.9570170895908856\n","09/11/2024 18:33:54 - INFO - trainer -     slot_precision = 0.9515962924819773\n","09/11/2024 18:33:54 - INFO - trainer -     slot_recall = 0.9625\n","mean_intent_slot increased (0.905620 --> 0.907080).  Saving model ...\n","Iteration: 100% 56/56 [00:27<00:00,  2.06it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:34:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:34:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:34:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.68it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.68it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.77it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.14it/s]\n","09/11/2024 18:34:21 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:34:21 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:34:21 - INFO - trainer -     loss = 1.2910365256746965\n","09/11/2024 18:34:21 - INFO - trainer -     mean_intent_slot = 0.8969155844155844\n","09/11/2024 18:34:21 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 18:34:21 - INFO - trainer -     slot_f1 = 0.9545454545454545\n","09/11/2024 18:34:21 - INFO - trainer -     slot_precision = 0.9467213114754098\n","09/11/2024 18:34:21 - INFO - trainer -     slot_recall = 0.9625\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:34:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:34:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:34:39 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.69it/s]\n","09/11/2024 18:34:41 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:34:41 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 18:34:41 - INFO - trainer -     loss = 1.2680891410979842\n","09/11/2024 18:34:41 - INFO - trainer -     mean_intent_slot = 0.902241017979877\n","09/11/2024 18:34:41 - INFO - trainer -     semantic_frame_acc = 0.7346938775510204\n","09/11/2024 18:34:41 - INFO - trainer -     slot_f1 = 0.9549922400413865\n","09/11/2024 18:34:41 - INFO - trainer -     slot_precision = 0.9486125385405961\n","09/11/2024 18:34:41 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:35:00 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:35:00 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:35:00 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.62it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.62it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.59it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.06it/s]\n","09/11/2024 18:35:02 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:35:02 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:35:02 - INFO - trainer -     loss = 1.2834989457457726\n","09/11/2024 18:35:02 - INFO - trainer -     mean_intent_slot = 0.8956118493909191\n","09/11/2024 18:35:02 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 18:35:02 - INFO - trainer -     slot_f1 = 0.951937984496124\n","09/11/2024 18:35:02 - INFO - trainer -     slot_precision = 0.9446153846153846\n","09/11/2024 18:35:02 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:35:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:35:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:35:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:35:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:35:22 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:35:22 - INFO - trainer -     loss = 1.2803669608796813\n","09/11/2024 18:35:22 - INFO - trainer -     mean_intent_slot = 0.8968873595950008\n","09/11/2024 18:35:22 - INFO - trainer -     semantic_frame_acc = 0.7244897959183674\n","09/11/2024 18:35:22 - INFO - trainer -     slot_f1 = 0.951937984496124\n","09/11/2024 18:35:22 - INFO - trainer -     slot_precision = 0.9446153846153846\n","09/11/2024 18:35:22 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:35:41 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:35:41 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:35:41 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.53it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.47it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.53it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.60it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.51it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.01it/s]\n","09/11/2024 18:35:43 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:35:43 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:35:43 - INFO - trainer -     loss = 1.2960458985928978\n","09/11/2024 18:35:43 - INFO - trainer -     mean_intent_slot = 0.8949005891016201\n","09/11/2024 18:35:43 - INFO - trainer -     semantic_frame_acc = 0.7117346938775511\n","09/11/2024 18:35:43 - INFO - trainer -     slot_f1 = 0.9505154639175258\n","09/11/2024 18:35:43 - INFO - trainer -     slot_precision = 0.9408163265306122\n","09/11/2024 18:35:43 - INFO - trainer -     slot_recall = 0.9604166666666667\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:36:02 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:36:02 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:36:02 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:36:04 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:36:04 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:36:04 - INFO - trainer -     loss = 1.3076669754726546\n","09/11/2024 18:36:04 - INFO - trainer -     mean_intent_slot = 0.8931374531284464\n","09/11/2024 18:36:04 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 18:36:04 - INFO - trainer -     slot_f1 = 0.9469891919711786\n","09/11/2024 18:36:04 - INFO - trainer -     slot_precision = 0.9359104781281791\n","09/11/2024 18:36:04 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:18<00:00,  2.83it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:36:23 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:36:23 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:36:23 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:36:24 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:36:24 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:36:24 - INFO - trainer -     loss = 1.305421500666333\n","09/11/2024 18:36:24 - INFO - trainer -     mean_intent_slot = 0.8936253403989107\n","09/11/2024 18:36:24 - INFO - trainer -     semantic_frame_acc = 0.7117346938775511\n","09/11/2024 18:36:24 - INFO - trainer -     slot_f1 = 0.9479649665121073\n","09/11/2024 18:36:24 - INFO - trainer -     slot_precision = 0.9378185524974516\n","09/11/2024 18:36:24 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.71it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:36:43 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:36:43 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:36:43 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:36:45 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:36:45 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:36:45 - INFO - trainer -     loss = 1.3030086073558778\n","09/11/2024 18:36:45 - INFO - trainer -     mean_intent_slot = 0.8974786517798061\n","09/11/2024 18:36:45 - INFO - trainer -     semantic_frame_acc = 0.7168367346938775\n","09/11/2024 18:36:45 - INFO - trainer -     slot_f1 = 0.9480185280494082\n","09/11/2024 18:36:45 - INFO - trainer -     slot_precision = 0.9369277721261444\n","09/11/2024 18:36:45 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:37:04 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:37:04 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:37:04 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.16it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.67it/s]\n","09/11/2024 18:37:05 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:37:05 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:37:05 - INFO - trainer -     loss = 1.2997589817137591\n","09/11/2024 18:37:05 - INFO - trainer -     mean_intent_slot = 0.8990281202455275\n","09/11/2024 18:37:05 - INFO - trainer -     semantic_frame_acc = 0.7193877551020408\n","09/11/2024 18:37:05 - INFO - trainer -     slot_f1 = 0.9460154241645244\n","09/11/2024 18:37:05 - INFO - trainer -     slot_precision = 0.934010152284264\n","09/11/2024 18:37:05 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:37:24 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:37:24 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:37:24 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.69it/s]\n","09/11/2024 18:37:26 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:37:26 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:37:26 - INFO - trainer -     loss = 1.2800480967187988\n","09/11/2024 18:37:26 - INFO - trainer -     mean_intent_slot = 0.9020387134761169\n","09/11/2024 18:37:26 - INFO - trainer -     semantic_frame_acc = 0.7244897959183674\n","09/11/2024 18:37:26 - INFO - trainer -     slot_f1 = 0.9469345698093766\n","09/11/2024 18:37:26 - INFO - trainer -     slot_precision = 0.9367991845056065\n","09/11/2024 18:37:26 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:18<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:37:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:37:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:37:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 18:37:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:37:47 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:37:47 - INFO - trainer -     loss = 1.2929652860454683\n","09/11/2024 18:37:47 - INFO - trainer -     mean_intent_slot = 0.904048971163065\n","09/11/2024 18:37:47 - INFO - trainer -     semantic_frame_acc = 0.7321428571428571\n","09/11/2024 18:37:47 - INFO - trainer -     slot_f1 = 0.950955085183273\n","09/11/2024 18:37:47 - INFO - trainer -     slot_precision = 0.9426816786079836\n","09/11/2024 18:37:47 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:18<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:38:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:38:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:38:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.05it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.06it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.12it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 18:38:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:38:07 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:38:07 - INFO - trainer -     loss = 1.3040411993528582\n","09/11/2024 18:38:07 - INFO - trainer -     mean_intent_slot = 0.9045404208194905\n","09/11/2024 18:38:07 - INFO - trainer -     semantic_frame_acc = 0.7346938775510204\n","09/11/2024 18:38:07 - INFO - trainer -     slot_f1 = 0.951937984496124\n","09/11/2024 18:38:07 - INFO - trainer -     slot_precision = 0.9446153846153846\n","09/11/2024 18:38:07 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:38:27 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:38:27 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:38:27 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:38:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:38:28 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:38:28 - INFO - trainer -     loss = 1.3075717917111302\n","09/11/2024 18:38:28 - INFO - trainer -     mean_intent_slot = 0.9037524006500222\n","09/11/2024 18:38:28 - INFO - trainer -     semantic_frame_acc = 0.7321428571428571\n","09/11/2024 18:38:28 - INFO - trainer -     slot_f1 = 0.9503619441571871\n","09/11/2024 18:38:28 - INFO - trainer -     slot_precision = 0.9435318275154004\n","09/11/2024 18:38:28 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:38:47 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:38:47 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:38:47 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.87it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.29it/s]\n","09/11/2024 18:38:49 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:38:49 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:38:49 - INFO - trainer -     loss = 1.3057911803812854\n","09/11/2024 18:38:49 - INFO - trainer -     mean_intent_slot = 0.9045404208194905\n","09/11/2024 18:38:49 - INFO - trainer -     semantic_frame_acc = 0.7346938775510204\n","09/11/2024 18:38:49 - INFO - trainer -     slot_f1 = 0.951937984496124\n","09/11/2024 18:38:49 - INFO - trainer -     slot_precision = 0.9446153846153846\n","09/11/2024 18:38:49 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:39:08 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:39:08 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:39:08 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 18:39:09 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:39:09 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:39:09 - INFO - trainer -     loss = 1.30308749742939\n","09/11/2024 18:39:09 - INFO - trainer -     mean_intent_slot = 0.9037780401416766\n","09/11/2024 18:39:09 - INFO - trainer -     semantic_frame_acc = 0.7321428571428571\n","09/11/2024 18:39:09 - INFO - trainer -     slot_f1 = 0.950413223140496\n","09/11/2024 18:39:09 - INFO - trainer -     slot_precision = 0.9426229508196722\n","09/11/2024 18:39:09 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:39:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:39:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:39:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.69it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.22it/s]\n","09/11/2024 18:39:30 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:39:30 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:39:30 - INFO - trainer -     loss = 1.3050426548080785\n","09/11/2024 18:39:30 - INFO - trainer -     mean_intent_slot = 0.9032615112160567\n","09/11/2024 18:39:30 - INFO - trainer -     semantic_frame_acc = 0.7295918367346939\n","09/11/2024 18:39:30 - INFO - trainer -     slot_f1 = 0.9493801652892562\n","09/11/2024 18:39:30 - INFO - trainer -     slot_precision = 0.9415983606557377\n","09/11/2024 18:39:30 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 16 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:39:49 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:39:49 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:39:49 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.07it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.62it/s]\n","09/11/2024 18:39:51 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:39:51 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:39:51 - INFO - trainer -     loss = 1.3072419261360275\n","09/11/2024 18:39:51 - INFO - trainer -     mean_intent_slot = 0.9027449822904368\n","09/11/2024 18:39:51 - INFO - trainer -     semantic_frame_acc = 0.7295918367346939\n","09/11/2024 18:39:51 - INFO - trainer -     slot_f1 = 0.9483471074380165\n","09/11/2024 18:39:51 - INFO - trainer -     slot_precision = 0.9405737704918032\n","09/11/2024 18:39:51 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 17 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:40:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:40:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:40:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.45it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.58it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.12it/s]\n","09/11/2024 18:40:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:40:12 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:40:12 - INFO - trainer -     loss = 1.3106536116850163\n","09/11/2024 18:40:12 - INFO - trainer -     mean_intent_slot = 0.9025001843793791\n","09/11/2024 18:40:12 - INFO - trainer -     semantic_frame_acc = 0.7295918367346939\n","09/11/2024 18:40:12 - INFO - trainer -     slot_f1 = 0.947857511615901\n","09/11/2024 18:40:12 - INFO - trainer -     slot_precision = 0.9396110542476971\n","09/11/2024 18:40:12 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 18 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:40:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:40:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:40:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.69it/s]\n","09/11/2024 18:40:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:40:32 - INFO - trainer -     intent_acc = 0.8571428571428571\n","09/11/2024 18:40:32 - INFO - trainer -     loss = 1.3108874620603663\n","09/11/2024 18:40:32 - INFO - trainer -     mean_intent_slot = 0.9025001843793791\n","09/11/2024 18:40:32 - INFO - trainer -     semantic_frame_acc = 0.7295918367346939\n","09/11/2024 18:40:32 - INFO - trainer -     slot_f1 = 0.947857511615901\n","09/11/2024 18:40:32 - INFO - trainer -     slot_precision = 0.9396110542476971\n","09/11/2024 18:40:32 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 19 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Epoch: 100% 50/50 [17:50<00:00, 21.41s/it]\n","09/11/2024 18:40:33 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 18:40:33 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 18:40:33 - INFO - trainer -     Num examples = 346\n","09/11/2024 18:40:33 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.63it/s]\n","09/11/2024 18:40:34 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:40:34 - INFO - trainer -     intent_acc = 0.861271676300578\n","09/11/2024 18:40:34 - INFO - trainer -     loss = 1.3903634548187256\n","09/11/2024 18:40:34 - INFO - trainer -     mean_intent_slot = 0.9014129736673089\n","09/11/2024 18:40:34 - INFO - trainer -     semantic_frame_acc = 0.7023121387283237\n","09/11/2024 18:40:34 - INFO - trainer -     slot_f1 = 0.9415542710340399\n","09/11/2024 18:40:34 - INFO - trainer -     slot_precision = 0.9361430395913155\n","09/11/2024 18:40:34 - INFO - trainer -     slot_recall = 0.9470284237726099\n"]}]},{"cell_type":"code","source":["# First, run the previous bash script to train JointBERT-CRF_PhoBERTencoder\n","# !bash run_jointBERT-CRF_PhoBERTencoder.sh\n","\n","# Now set up environment variables for the new training run\n","lr = \"4e-5\"\n","c = \"0.8\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Set the MODEL_DIR path for JointIDSF\n","MODEL_DIR = f\"Model_Hackathon/JointIDSF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Run the second python script using the pretrained model path\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_intent_context_attention \\\n","                  --attention_embedding_size 200 \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --pretrained \\\n","                  --pretrained_path Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"QCRTF6lbaePw","executionInfo":{"status":"ok","timestamp":1726081549211,"user_tz":-420,"elapsed":1050546,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"b933db08-84e3-4fd8-90be-2f097232c141"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["4e-5\n","Model_Hackathon/JointIDSF_CLPhoBERTencoder/4e-5/0.8/100\n","2024-09-11 18:48:31.117072: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 18:48:31.141173: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 18:48:31.147800: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 18:48:31.164522: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 18:48:32.553823: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","09/11/2024 18:48:34 - INFO - data_loader -   Loading features from cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","/content/ViNLU/data_loader.py:238: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n","  features = torch.load(cached_features_file)\n","09/11/2024 18:48:34 - INFO - data_loader -   Loading features from cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 18:48:34 - INFO - data_loader -   Loading features from cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","phongtintruong/clphobert-base-16-256-50-30\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 and are newly initialized: ['slot_classifier.attention.linear_out.weight', 'slot_classifier.linear_intent_context.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 18:48:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:48:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:48:34 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:02<00:00,  2.98it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 18:48:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:48:37 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 18:48:37 - INFO - trainer -     loss = 8.467852864946638\n","09/11/2024 18:48:37 - INFO - trainer -     mean_intent_slot = 0.4339380645369787\n","09/11/2024 18:48:37 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 18:48:37 - INFO - trainer -     slot_f1 = 0.015835312747426764\n","09/11/2024 18:48:37 - INFO - trainer -     slot_precision = 0.010604453870625663\n","09/11/2024 18:48:37 - INFO - trainer -     slot_recall = 0.03125\n","{'loss': 8.467852864946638, 'intent_acc': 0.8520408163265306, 'slot_precision': 0.010604453870625663, 'slot_recall': 0.03125, 'slot_f1': 0.015835312747426764, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.4339380645369787}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 18:48:37 - INFO - trainer -   ***** Running training *****\n","09/11/2024 18:48:37 - INFO - trainer -     Num examples = 1790\n","09/11/2024 18:48:37 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 18:48:37 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 18:48:37 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 18:48:37 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 18:48:37 - INFO - trainer -     Logging steps = 56\n","09/11/2024 18:48:37 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:16<00:00,  3.17it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:48:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:48:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:48:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.92it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.36it/s]\n","09/11/2024 18:48:56 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:48:56 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 18:48:56 - INFO - trainer -     loss = 3.201299020222255\n","09/11/2024 18:48:56 - INFO - trainer -     mean_intent_slot = 0.8422832969665854\n","09/11/2024 18:48:56 - INFO - trainer -     semantic_frame_acc = 0.3010204081632653\n","09/11/2024 18:48:56 - INFO - trainer -     slot_f1 = 0.860587002096436\n","09/11/2024 18:48:56 - INFO - trainer -     slot_precision = 0.8660337552742616\n","09/11/2024 18:48:56 - INFO - trainer -     slot_recall = 0.8552083333333333\n","mean_intent_slot increased (inf --> 0.842283).  Saving model ...\n","Iteration: 100% 56/56 [00:25<00:00,  2.24it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:17<00:00,  3.09it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:49:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:49:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:49:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.73it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.82it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.84it/s]\u001b[A\n","Evaluating:  86% 6/7 [00:01<00:00,  3.84it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.19it/s]\n","09/11/2024 18:49:21 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:49:21 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:49:21 - INFO - trainer -     loss = 1.8956199543816703\n","09/11/2024 18:49:21 - INFO - trainer -     mean_intent_slot = 0.8843080242849828\n","09/11/2024 18:49:21 - INFO - trainer -     semantic_frame_acc = 0.6224489795918368\n","09/11/2024 18:49:21 - INFO - trainer -     slot_f1 = 0.9267793138760881\n","09/11/2024 18:49:21 - INFO - trainer -     slot_precision = 0.9113796576032226\n","09/11/2024 18:49:21 - INFO - trainer -     slot_recall = 0.9427083333333334\n","mean_intent_slot increased (0.842283 --> 0.884308).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.52it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:17<00:00,  3.16it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:49:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:49:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:49:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.38it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.39it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.44it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.49it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.53it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.04it/s]\n","09/11/2024 18:49:43 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:49:43 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:49:43 - INFO - trainer -     loss = 1.5033823304942675\n","09/11/2024 18:49:43 - INFO - trainer -     mean_intent_slot = 0.8791820006691201\n","09/11/2024 18:49:43 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 18:49:43 - INFO - trainer -     slot_f1 = 0.9241803278688525\n","09/11/2024 18:49:43 - INFO - trainer -     slot_precision = 0.9092741935483871\n","09/11/2024 18:49:43 - INFO - trainer -     slot_recall = 0.9395833333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.91it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:17<00:00,  3.23it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:50:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:50:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:50:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.38it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.46it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.48it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.51it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.52it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.04it/s]\n","09/11/2024 18:50:02 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:50:02 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 18:50:02 - INFO - trainer -     loss = 1.5306620353034563\n","09/11/2024 18:50:02 - INFO - trainer -     mean_intent_slot = 0.863395076556723\n","09/11/2024 18:50:02 - INFO - trainer -     semantic_frame_acc = 0.6122448979591837\n","09/11/2024 18:50:02 - INFO - trainer -     slot_f1 = 0.9181166837256909\n","09/11/2024 18:50:02 - INFO - trainer -     slot_precision = 0.9024144869215291\n","09/11/2024 18:50:02 - INFO - trainer -     slot_recall = 0.934375\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.94it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:17<00:00,  3.19it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:50:20 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:50:20 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:50:20 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.78it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.80it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.90it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.90it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.38it/s]\n","09/11/2024 18:50:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:50:22 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 18:50:22 - INFO - trainer -     loss = 1.855204505579812\n","09/11/2024 18:50:22 - INFO - trainer -     mean_intent_slot = 0.8670597682658845\n","09/11/2024 18:50:22 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 18:50:22 - INFO - trainer -     slot_f1 = 0.9407521895929933\n","09/11/2024 18:50:22 - INFO - trainer -     slot_precision = 0.9306829765545361\n","09/11/2024 18:50:22 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.87it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:17<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:50:40 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:50:40 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:50:40 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.41it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.44it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.93it/s]\n","09/11/2024 18:50:42 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:50:42 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 18:50:42 - INFO - trainer -     loss = 1.5659355534506696\n","09/11/2024 18:50:42 - INFO - trainer -     mean_intent_slot = 0.875789164586698\n","09/11/2024 18:50:42 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 18:50:42 - INFO - trainer -     slot_f1 = 0.9352517985611511\n","09/11/2024 18:50:42 - INFO - trainer -     slot_precision = 0.922920892494929\n","09/11/2024 18:50:42 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.85it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:17<00:00,  3.12it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:51:00 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:51:00 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:51:00 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 18:51:01 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:51:01 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:51:01 - INFO - trainer -     loss = 1.3589144255965948\n","09/11/2024 18:51:01 - INFO - trainer -     mean_intent_slot = 0.8788540596094552\n","09/11/2024 18:51:01 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 18:51:01 - INFO - trainer -     slot_f1 = 0.9362795477903391\n","09/11/2024 18:51:01 - INFO - trainer -     slot_precision = 0.9239350912778904\n","09/11/2024 18:51:01 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.85it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:17<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:51:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:51:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:51:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.94it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.87it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.82it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.28it/s]\n","09/11/2024 18:51:21 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:51:21 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 18:51:21 - INFO - trainer -     loss = 1.3895030319690704\n","09/11/2024 18:51:21 - INFO - trainer -     mean_intent_slot = 0.8820928887018725\n","09/11/2024 18:51:21 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:51:21 - INFO - trainer -     slot_f1 = 0.9402061855670103\n","09/11/2024 18:51:21 - INFO - trainer -     slot_precision = 0.9306122448979591\n","09/11/2024 18:51:21 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:18<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:51:40 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:51:40 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:51:40 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 18:51:41 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:51:41 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:51:41 - INFO - trainer -     loss = 1.169009247528655\n","09/11/2024 18:51:41 - INFO - trainer -     mean_intent_slot = 0.8870620464707175\n","09/11/2024 18:51:41 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:51:41 - INFO - trainer -     slot_f1 = 0.9348383786557208\n","09/11/2024 18:51:41 - INFO - trainer -     slot_precision = 0.9211324570273003\n","09/11/2024 18:51:41 - INFO - trainer -     slot_recall = 0.9489583333333333\n","mean_intent_slot increased (0.884308 --> 0.887062).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.46it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:52:03 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:52:03 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:52:03 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.90it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.93it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.34it/s]\n","09/11/2024 18:52:04 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:52:04 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 18:52:04 - INFO - trainer -     loss = 1.3385532349348068\n","09/11/2024 18:52:04 - INFO - trainer -     mean_intent_slot = 0.885532411092362\n","09/11/2024 18:52:04 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:52:04 - INFO - trainer -     slot_f1 = 0.9266770670826833\n","09/11/2024 18:52:04 - INFO - trainer -     slot_precision = 0.9252336448598131\n","09/11/2024 18:52:04 - INFO - trainer -     slot_recall = 0.928125\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:52:23 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:52:23 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:52:23 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.10it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.62it/s]\n","09/11/2024 18:52:25 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:52:25 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:52:25 - INFO - trainer -     loss = 1.3721588677061456\n","09/11/2024 18:52:25 - INFO - trainer -     mean_intent_slot = 0.8830113724879265\n","09/11/2024 18:52:25 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 18:52:25 - INFO - trainer -     slot_f1 = 0.9190839694656489\n","09/11/2024 18:52:25 - INFO - trainer -     slot_precision = 0.8985074626865671\n","09/11/2024 18:52:25 - INFO - trainer -     slot_recall = 0.940625\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:52:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:52:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:52:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.97it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.01it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.06it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.97it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.40it/s]\n","09/11/2024 18:52:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:52:46 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 18:52:46 - INFO - trainer -     loss = 1.6255581810006074\n","09/11/2024 18:52:46 - INFO - trainer -     mean_intent_slot = 0.8806507312405085\n","09/11/2024 18:52:46 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 18:52:46 - INFO - trainer -     slot_f1 = 0.9245667686034659\n","09/11/2024 18:52:46 - INFO - trainer -     slot_precision = 0.9051896207584831\n","09/11/2024 18:52:46 - INFO - trainer -     slot_recall = 0.9447916666666667\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:21<00:00,  2.66it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:19<00:00,  2.83it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:53:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:53:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:53:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 18:53:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:53:07 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 18:53:07 - INFO - trainer -     loss = 1.6143439881769674\n","09/11/2024 18:53:07 - INFO - trainer -     mean_intent_slot = 0.8786062986345617\n","09/11/2024 18:53:07 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 18:53:07 - INFO - trainer -     slot_f1 = 0.9383350462487153\n","09/11/2024 18:53:07 - INFO - trainer -     slot_precision = 0.9259634888438134\n","09/11/2024 18:53:07 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.68it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:53:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:53:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:53:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.15it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 18:53:27 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:53:27 - INFO - trainer -     intent_acc = 0.8112244897959183\n","09/11/2024 18:53:27 - INFO - trainer -     loss = 1.6278155551158957\n","09/11/2024 18:53:27 - INFO - trainer -     mean_intent_slot = 0.8736863952584123\n","09/11/2024 18:53:27 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 18:53:27 - INFO - trainer -     slot_f1 = 0.9361483007209063\n","09/11/2024 18:53:27 - INFO - trainer -     slot_precision = 0.9256619144602851\n","09/11/2024 18:53:27 - INFO - trainer -     slot_recall = 0.946875\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:53:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:53:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:53:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.42it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.51it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.66it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.66it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.10it/s]\n","09/11/2024 18:53:48 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:53:48 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 18:53:48 - INFO - trainer -     loss = 1.5299497552748238\n","09/11/2024 18:53:48 - INFO - trainer -     mean_intent_slot = 0.8752280278417395\n","09/11/2024 18:53:48 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:53:48 - INFO - trainer -     slot_f1 = 0.9417825862957238\n","09/11/2024 18:53:48 - INFO - trainer -     slot_precision = 0.9317023445463812\n","09/11/2024 18:53:48 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:21<00:00,  2.66it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:18<00:00,  2.97it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:54:07 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:54:07 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:54:07 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.08it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.10it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.61it/s]\n","09/11/2024 18:54:09 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:54:09 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 18:54:09 - INFO - trainer -     loss = 1.584543077408203\n","09/11/2024 18:54:09 - INFO - trainer -     mean_intent_slot = 0.871575574958745\n","09/11/2024 18:54:09 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 18:54:09 - INFO - trainer -     slot_f1 = 0.9293756397134084\n","09/11/2024 18:54:09 - INFO - trainer -     slot_precision = 0.9134808853118712\n","09/11/2024 18:54:09 - INFO - trainer -     slot_recall = 0.9458333333333333\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:54:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:54:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:54:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.66it/s]\n","09/11/2024 18:54:29 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:54:29 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 18:54:29 - INFO - trainer -     loss = 1.526871835546834\n","09/11/2024 18:54:29 - INFO - trainer -     mean_intent_slot = 0.8754768385211963\n","09/11/2024 18:54:29 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 18:54:29 - INFO - trainer -     slot_f1 = 0.9371781668383109\n","09/11/2024 18:54:29 - INFO - trainer -     slot_precision = 0.9266802443991853\n","09/11/2024 18:54:29 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:54:49 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:54:49 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:54:49 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.16it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 18:54:50 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:54:50 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:54:50 - INFO - trainer -     loss = 1.597581360622176\n","09/11/2024 18:54:50 - INFO - trainer -     mean_intent_slot = 0.880575182159417\n","09/11/2024 18:54:50 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:54:50 - INFO - trainer -     slot_f1 = 0.9397217928902627\n","09/11/2024 18:54:50 - INFO - trainer -     slot_precision = 0.9296636085626911\n","09/11/2024 18:54:50 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.71it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:55:09 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:55:09 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:55:09 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.23it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 18:55:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:55:10 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 18:55:10 - INFO - trainer -     loss = 1.4834384812441255\n","09/11/2024 18:55:10 - INFO - trainer -     mean_intent_slot = 0.8886331185472651\n","09/11/2024 18:55:10 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 18:55:10 - INFO - trainer -     slot_f1 = 0.9379805228088159\n","09/11/2024 18:55:10 - INFO - trainer -     slot_precision = 0.9233097880928355\n","09/11/2024 18:55:10 - INFO - trainer -     slot_recall = 0.953125\n","mean_intent_slot increased (0.887062 --> 0.888633).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.49it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:55:32 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:55:32 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:55:32 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:55:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:55:33 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 18:55:33 - INFO - trainer -     loss = 1.6549801799867834\n","09/11/2024 18:55:33 - INFO - trainer -     mean_intent_slot = 0.8794001173364623\n","09/11/2024 18:55:33 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 18:55:33 - INFO - trainer -     slot_f1 = 0.9373716632443532\n","09/11/2024 18:55:33 - INFO - trainer -     slot_precision = 0.9240890688259109\n","09/11/2024 18:55:33 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:55:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:55:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:55:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.20it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:55:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:55:53 - INFO - trainer -     intent_acc = 0.8112244897959183\n","09/11/2024 18:55:53 - INFO - trainer -     loss = 1.65951477656407\n","09/11/2024 18:55:53 - INFO - trainer -     mean_intent_slot = 0.872758035452374\n","09/11/2024 18:55:53 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 18:55:53 - INFO - trainer -     slot_f1 = 0.9342915811088296\n","09/11/2024 18:55:53 - INFO - trainer -     slot_precision = 0.9210526315789473\n","09/11/2024 18:55:53 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:18<00:00,  2.82it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:56:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:56:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:56:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.09it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 18:56:14 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:56:14 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 18:56:14 - INFO - trainer -     loss = 1.5886366690642066\n","09/11/2024 18:56:14 - INFO - trainer -     mean_intent_slot = 0.8814704343275772\n","09/11/2024 18:56:14 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 18:56:14 - INFO - trainer -     slot_f1 = 0.9364102564102564\n","09/11/2024 18:56:14 - INFO - trainer -     slot_precision = 0.9222222222222223\n","09/11/2024 18:56:14 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:56:33 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:56:33 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:56:33 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.80it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 18:56:34 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:56:34 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 18:56:34 - INFO - trainer -     loss = 1.6165576623752713\n","09/11/2024 18:56:34 - INFO - trainer -     mean_intent_slot = 0.8811831813279443\n","09/11/2024 18:56:34 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 18:56:34 - INFO - trainer -     slot_f1 = 0.9307337095946641\n","09/11/2024 18:56:34 - INFO - trainer -     slot_precision = 0.917087967644085\n","09/11/2024 18:56:34 - INFO - trainer -     slot_recall = 0.9447916666666667\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:18<00:00,  2.93it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:56:53 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:56:53 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:56:53 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.70it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.73it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.73it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.73it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.20it/s]\n","09/11/2024 18:56:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:56:55 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:56:55 - INFO - trainer -     loss = 1.551565904835505\n","09/11/2024 18:56:55 - INFO - trainer -     mean_intent_slot = 0.8902640654407048\n","09/11/2024 18:56:55 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 18:56:55 - INFO - trainer -     slot_f1 = 0.9386913961875322\n","09/11/2024 18:56:55 - INFO - trainer -     slot_precision = 0.928644240570846\n","09/11/2024 18:56:55 - INFO - trainer -     slot_recall = 0.9489583333333333\n","mean_intent_slot increased (0.888633 --> 0.890264).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.46it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:57:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:57:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:57:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 18:57:17 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:57:17 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:57:17 - INFO - trainer -     loss = 1.5202103748119302\n","09/11/2024 18:57:17 - INFO - trainer -     mean_intent_slot = 0.8910522499422014\n","09/11/2024 18:57:17 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 18:57:17 - INFO - trainer -     slot_f1 = 0.9402677651905254\n","09/11/2024 18:57:17 - INFO - trainer -     slot_precision = 0.929735234215886\n","09/11/2024 18:57:17 - INFO - trainer -     slot_recall = 0.9510416666666667\n","mean_intent_slot increased (0.890264 --> 0.891052).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.49it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:18<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:57:38 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:57:38 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:57:38 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 18:57:40 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:57:40 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:57:40 - INFO - trainer -     loss = 1.430047082814521\n","09/11/2024 18:57:40 - INFO - trainer -     mean_intent_slot = 0.8935724805386072\n","09/11/2024 18:57:40 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 18:57:40 - INFO - trainer -     slot_f1 = 0.9402061855670103\n","09/11/2024 18:57:40 - INFO - trainer -     slot_precision = 0.9306122448979591\n","09/11/2024 18:57:40 - INFO - trainer -     slot_recall = 0.95\n","mean_intent_slot increased (0.891052 --> 0.893572).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.47it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:58:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:58:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:58:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.10it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.61it/s]\n","09/11/2024 18:58:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:58:03 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 18:58:03 - INFO - trainer -     loss = 1.431541655811348\n","09/11/2024 18:58:03 - INFO - trainer -     mean_intent_slot = 0.8925678518830212\n","09/11/2024 18:58:03 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 18:58:03 - INFO - trainer -     slot_f1 = 0.9432989690721649\n","09/11/2024 18:58:03 - INFO - trainer -     slot_precision = 0.9336734693877551\n","09/11/2024 18:58:03 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:58:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:58:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:58:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.24it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 18:58:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:58:23 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:58:23 - INFO - trainer -     loss = 1.4518970257070447\n","09/11/2024 18:58:23 - INFO - trainer -     mean_intent_slot = 0.8918173033495436\n","09/11/2024 18:58:23 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:58:23 - INFO - trainer -     slot_f1 = 0.936695831188883\n","09/11/2024 18:58:23 - INFO - trainer -     slot_precision = 0.9257375381485249\n","09/11/2024 18:58:23 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:58:41 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:58:41 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:58:41 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 18:58:43 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:58:43 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 18:58:43 - INFO - trainer -     loss = 1.4364088883490436\n","09/11/2024 18:58:43 - INFO - trainer -     mean_intent_slot = 0.8921230362648658\n","09/11/2024 18:58:43 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 18:58:43 - INFO - trainer -     slot_f1 = 0.9373072970195273\n","09/11/2024 18:58:43 - INFO - trainer -     slot_precision = 0.9249492900608519\n","09/11/2024 18:58:43 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:59:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:59:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:59:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.28it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 18:59:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:59:03 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 18:59:03 - INFO - trainer -     loss = 1.4986772571490812\n","09/11/2024 18:59:03 - INFO - trainer -     mean_intent_slot = 0.8903467813860764\n","09/11/2024 18:59:03 - INFO - trainer -     semantic_frame_acc = 0.701530612244898\n","09/11/2024 18:59:03 - INFO - trainer -     slot_f1 = 0.9439588688946016\n","09/11/2024 18:59:03 - INFO - trainer -     slot_precision = 0.9319796954314721\n","09/11/2024 18:59:03 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:59:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:59:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:59:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 18:59:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:59:23 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:59:23 - INFO - trainer -     loss = 1.5242169841325708\n","09/11/2024 18:59:23 - INFO - trainer -     mean_intent_slot = 0.8887996556647351\n","09/11/2024 18:59:23 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 18:59:23 - INFO - trainer -     slot_f1 = 0.9434156378600823\n","09/11/2024 18:59:23 - INFO - trainer -     slot_precision = 0.931910569105691\n","09/11/2024 18:59:23 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 18:59:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 18:59:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 18:59:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.51it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.62it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.86it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.35it/s]\n","09/11/2024 18:59:43 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 18:59:43 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 18:59:43 - INFO - trainer -     loss = 1.5265346977394074\n","09/11/2024 18:59:43 - INFO - trainer -     mean_intent_slot = 0.8883444034698068\n","09/11/2024 18:59:43 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 18:59:43 - INFO - trainer -     slot_f1 = 0.9425051334702259\n","09/11/2024 18:59:43 - INFO - trainer -     slot_precision = 0.9291497975708503\n","09/11/2024 18:59:43 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:00:02 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:00:02 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:00:02 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.20it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:00:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:00:03 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:00:03 - INFO - trainer -     loss = 1.5115276749711484\n","09/11/2024 19:00:03 - INFO - trainer -     mean_intent_slot = 0.8870456117732146\n","09/11/2024 19:00:03 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:00:03 - INFO - trainer -     slot_f1 = 0.9399075500770416\n","09/11/2024 19:00:03 - INFO - trainer -     slot_precision = 0.9270516717325228\n","09/11/2024 19:00:03 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  2.95it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:00:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:00:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:00:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.86it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.27it/s]\n","09/11/2024 19:00:24 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:00:24 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 19:00:24 - INFO - trainer -     loss = 1.5242851691187493\n","09/11/2024 19:00:24 - INFO - trainer -     mean_intent_slot = 0.8809802609568418\n","09/11/2024 19:00:24 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:00:24 - INFO - trainer -     slot_f1 = 0.930327868852459\n","09/11/2024 19:00:24 - INFO - trainer -     slot_precision = 0.9153225806451613\n","09/11/2024 19:00:24 - INFO - trainer -     slot_recall = 0.9458333333333333\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:00:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:00:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:00:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.78it/s]\n","09/11/2024 19:00:44 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:00:44 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 19:00:44 - INFO - trainer -     loss = 1.524733854956659\n","09/11/2024 19:00:44 - INFO - trainer -     mean_intent_slot = 0.882243799621335\n","09/11/2024 19:00:44 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:00:44 - INFO - trainer -     slot_f1 = 0.9328549461814455\n","09/11/2024 19:00:44 - INFO - trainer -     slot_precision = 0.9182643794147326\n","09/11/2024 19:00:44 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:01:03 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:01:03 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:01:03 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.92it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.43it/s]\n","09/11/2024 19:01:04 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:01:04 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:01:04 - INFO - trainer -     loss = 1.5117954155762814\n","09/11/2024 19:01:04 - INFO - trainer -     mean_intent_slot = 0.8858097854526426\n","09/11/2024 19:01:04 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:01:04 - INFO - trainer -     slot_f1 = 0.9374358974358974\n","09/11/2024 19:01:04 - INFO - trainer -     slot_precision = 0.9232323232323232\n","09/11/2024 19:01:04 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:18<00:00,  2.93it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:01:23 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:01:23 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:01:23 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.70it/s]\n","09/11/2024 19:01:25 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:01:25 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:01:25 - INFO - trainer -     loss = 1.4961372146582497\n","09/11/2024 19:01:25 - INFO - trainer -     mean_intent_slot = 0.8880728331394191\n","09/11/2024 19:01:25 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 19:01:25 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:01:25 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:01:25 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:01:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:01:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:01:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.04it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.09it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 19:01:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:01:46 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:01:46 - INFO - trainer -     loss = 1.4997313308329987\n","09/11/2024 19:01:46 - INFO - trainer -     mean_intent_slot = 0.8890515975027543\n","09/11/2024 19:01:46 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:01:46 - INFO - trainer -     slot_f1 = 0.9388174807197943\n","09/11/2024 19:01:46 - INFO - trainer -     slot_precision = 0.9269035532994924\n","09/11/2024 19:01:46 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.71it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:19<00:00,  2.71it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:02:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:02:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:02:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.46it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.57it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.61it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.63it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.04it/s]\n","09/11/2024 19:02:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:02:07 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:02:07 - INFO - trainer -     loss = 1.4917242095606136\n","09/11/2024 19:02:07 - INFO - trainer -     mean_intent_slot = 0.8872687564234327\n","09/11/2024 19:02:07 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:02:07 - INFO - trainer -     slot_f1 = 0.9352517985611511\n","09/11/2024 19:02:07 - INFO - trainer -     slot_precision = 0.922920892494929\n","09/11/2024 19:02:07 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:21<00:00,  2.62it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:02:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:02:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:02:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.02it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.11it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.66it/s]\n","09/11/2024 19:02:27 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:02:27 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:02:27 - INFO - trainer -     loss = 1.5151666714809835\n","09/11/2024 19:02:27 - INFO - trainer -     mean_intent_slot = 0.8870209954485392\n","09/11/2024 19:02:27 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:02:27 - INFO - trainer -     slot_f1 = 0.9373072970195273\n","09/11/2024 19:02:27 - INFO - trainer -     slot_precision = 0.9249492900608519\n","09/11/2024 19:02:27 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:02:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:02:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:02:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.49it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.61it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.71it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.74it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.14it/s]\n","09/11/2024 19:02:48 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:02:48 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:02:48 - INFO - trainer -     loss = 1.514241861678394\n","09/11/2024 19:02:48 - INFO - trainer -     mean_intent_slot = 0.8888736263736263\n","09/11/2024 19:02:48 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 19:02:48 - INFO - trainer -     slot_f1 = 0.9384615384615383\n","09/11/2024 19:02:48 - INFO - trainer -     slot_precision = 0.9242424242424242\n","09/11/2024 19:02:48 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:18<00:00,  2.97it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:03:07 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:03:07 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:03:07 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.93it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.64it/s]\n","09/11/2024 19:03:09 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:03:09 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:03:09 - INFO - trainer -     loss = 1.5256763264270765\n","09/11/2024 19:03:09 - INFO - trainer -     mean_intent_slot = 0.886804362402045\n","09/11/2024 19:03:09 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:03:09 - INFO - trainer -     slot_f1 = 0.9394250513347023\n","09/11/2024 19:03:09 - INFO - trainer -     slot_precision = 0.9261133603238867\n","09/11/2024 19:03:09 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 16 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.71it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:03:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:03:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:03:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.17it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.71it/s]\n","09/11/2024 19:03:29 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:03:29 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:03:29 - INFO - trainer -     loss = 1.5259199371295316\n","09/11/2024 19:03:29 - INFO - trainer -     mean_intent_slot = 0.8870456117732146\n","09/11/2024 19:03:29 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:03:29 - INFO - trainer -     slot_f1 = 0.9399075500770416\n","09/11/2024 19:03:29 - INFO - trainer -     slot_precision = 0.9270516717325228\n","09/11/2024 19:03:29 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 17 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:18<00:00,  2.84it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:03:48 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:03:48 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:03:48 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.52it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.93it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.19it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 19:03:50 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:03:50 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:03:50 - INFO - trainer -     loss = 1.5300146463061017\n","09/11/2024 19:03:50 - INFO - trainer -     mean_intent_slot = 0.8870456117732146\n","09/11/2024 19:03:50 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:03:50 - INFO - trainer -     slot_f1 = 0.9399075500770416\n","09/11/2024 19:03:50 - INFO - trainer -     slot_precision = 0.9270516717325228\n","09/11/2024 19:03:50 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 18 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:04:09 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:04:09 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:04:09 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 19:04:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:04:10 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:04:10 - INFO - trainer -     loss = 1.5238943467515387\n","09/11/2024 19:04:10 - INFO - trainer -     mean_intent_slot = 0.8893483433435008\n","09/11/2024 19:04:10 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:04:10 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:04:10 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:04:10 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 19 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:18<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:04:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:04:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:04:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.66it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.60it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.54it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.50it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  3.97it/s]\n","09/11/2024 19:04:31 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:04:31 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:04:31 - INFO - trainer -     loss = 1.5257200374035165\n","09/11/2024 19:04:31 - INFO - trainer -     mean_intent_slot = 0.8893483433435008\n","09/11/2024 19:04:31 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:04:31 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:04:31 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:04:31 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 20 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:04:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:04:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:04:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.78it/s]\n","09/11/2024 19:04:51 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:04:51 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:04:51 - INFO - trainer -     loss = 1.5239375111913043\n","09/11/2024 19:04:51 - INFO - trainer -     mean_intent_slot = 0.8906238535475823\n","09/11/2024 19:04:51 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:04:51 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:04:51 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:04:51 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 21 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:05:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:05:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:05:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.85it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.85it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.28it/s]\n","09/11/2024 19:05:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:05:12 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:05:12 - INFO - trainer -     loss = 1.523943872257535\n","09/11/2024 19:05:12 - INFO - trainer -     mean_intent_slot = 0.8906238535475823\n","09/11/2024 19:05:12 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:05:12 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:05:12 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:05:12 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 22 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:18<00:00,  2.97it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:05:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:05:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:05:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.75it/s]\n","09/11/2024 19:05:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:05:33 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:05:33 - INFO - trainer -     loss = 1.5302186724896143\n","09/11/2024 19:05:33 - INFO - trainer -     mean_intent_slot = 0.8906238535475823\n","09/11/2024 19:05:33 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:05:33 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:05:33 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:05:33 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 23 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:05:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:05:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:05:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.94it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.17it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.74it/s]\n","09/11/2024 19:05:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:05:53 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:05:53 - INFO - trainer -     loss = 1.53035391456381\n","09/11/2024 19:05:53 - INFO - trainer -     mean_intent_slot = 0.8906238535475823\n","09/11/2024 19:05:53 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:05:53 - INFO - trainer -     slot_f1 = 0.9419619928094505\n","09/11/2024 19:05:53 - INFO - trainer -     slot_precision = 0.9290780141843972\n","09/11/2024 19:05:53 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 24 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Epoch: 100% 50/50 [17:16<00:00, 20.72s/it]\n","09/11/2024 19:05:53 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 19:05:53 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 19:05:53 - INFO - trainer -     Num examples = 346\n","09/11/2024 19:05:53 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.25it/s]\n","09/11/2024 19:05:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:05:55 - INFO - trainer -     intent_acc = 0.8554913294797688\n","09/11/2024 19:05:55 - INFO - trainer -     loss = 1.4644815623760223\n","09/11/2024 19:05:55 - INFO - trainer -     mean_intent_slot = 0.8998789126578857\n","09/11/2024 19:05:55 - INFO - trainer -     semantic_frame_acc = 0.708092485549133\n","09/11/2024 19:05:55 - INFO - trainer -     slot_f1 = 0.9442664958360024\n","09/11/2024 19:05:55 - INFO - trainer -     slot_precision = 0.9364675984752223\n","09/11/2024 19:05:55 - INFO - trainer -     slot_recall = 0.9521963824289406\n"]}]},{"cell_type":"code","source":["# First, run the previous bash script to train JointBERT-CRF_PhoBERTencoder\n","# !bash run_jointBERT-CRF_PhoBERTencoder.sh\n","\n","# Now set up environment variables for the new training run\n","lr = \"4e-5\"\n","c = \"0.6\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Set the MODEL_DIR path for JointIDSF\n","MODEL_DIR = f\"Model_Hackathon/JointIDSF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Run the second python script using the pretrained model path\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_intent_context_attention \\\n","                  --attention_embedding_size 200 \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --pretrained \\\n","                  --pretrained_path Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"atAjG5K1e-Dc","executionInfo":{"status":"ok","timestamp":1726082708514,"user_tz":-420,"elapsed":1042000,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"13db4b66-4aed-42b7-8c94-434b2e0aac1b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["4e-5\n","Model_Hackathon/JointIDSF_CLPhoBERTencoder/4e-5/0.6/100\n","2024-09-11 19:07:58.584114: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 19:07:58.605678: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 19:07:58.612068: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 19:07:58.627822: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 19:08:00.287581: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","09/11/2024 19:08:02 - INFO - data_loader -   Loading features from cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","/content/ViNLU/data_loader.py:238: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n","  features = torch.load(cached_features_file)\n","09/11/2024 19:08:03 - INFO - data_loader -   Loading features from cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 19:08:03 - INFO - data_loader -   Loading features from cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","phongtintruong/clphobert-base-16-256-50-30\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 and are newly initialized: ['slot_classifier.attention.linear_out.weight', 'slot_classifier.linear_intent_context.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 19:08:03 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:08:03 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:08:03 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:02<00:00,  3.23it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 19:08:05 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:08:05 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 19:08:05 - INFO - trainer -     loss = 15.937515258789062\n","09/11/2024 19:08:05 - INFO - trainer -     mean_intent_slot = 0.4339380645369787\n","09/11/2024 19:08:05 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 19:08:05 - INFO - trainer -     slot_f1 = 0.015835312747426764\n","09/11/2024 19:08:05 - INFO - trainer -     slot_precision = 0.010604453870625663\n","09/11/2024 19:08:05 - INFO - trainer -     slot_recall = 0.03125\n","{'loss': 15.937515258789062, 'intent_acc': 0.8520408163265306, 'slot_precision': 0.010604453870625663, 'slot_recall': 0.03125, 'slot_f1': 0.015835312747426764, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.4339380645369787}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 19:08:06 - INFO - trainer -   ***** Running training *****\n","09/11/2024 19:08:06 - INFO - trainer -     Num examples = 1790\n","09/11/2024 19:08:06 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 19:08:06 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 19:08:06 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 19:08:06 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 19:08:06 - INFO - trainer -     Logging steps = 56\n","09/11/2024 19:08:06 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:17<00:00,  3.20it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:08:23 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:08:23 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:08:23 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.39it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.48it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.42it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.44it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.48it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.04it/s]\n","09/11/2024 19:08:25 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:08:25 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 19:08:25 - INFO - trainer -     loss = 5.562477282115391\n","09/11/2024 19:08:25 - INFO - trainer -     mean_intent_slot = 0.856669758812616\n","09/11/2024 19:08:25 - INFO - trainer -     semantic_frame_acc = 0.32653061224489793\n","09/11/2024 19:08:25 - INFO - trainer -     slot_f1 = 0.8612987012987015\n","09/11/2024 19:08:25 - INFO - trainer -     slot_precision = 0.8590673575129534\n","09/11/2024 19:08:25 - INFO - trainer -     slot_recall = 0.8635416666666667\n","mean_intent_slot increased (inf --> 0.856670).  Saving model ...\n","Iteration: 100% 56/56 [00:21<00:00,  2.59it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:08:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:08:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:08:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.28it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:08:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:08:47 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:08:47 - INFO - trainer -     loss = 2.6939636937209537\n","09/11/2024 19:08:47 - INFO - trainer -     mean_intent_slot = 0.877826806398235\n","09/11/2024 19:08:47 - INFO - trainer -     semantic_frame_acc = 0.6147959183673469\n","09/11/2024 19:08:47 - INFO - trainer -     slot_f1 = 0.9189189189189189\n","09/11/2024 19:08:47 - INFO - trainer -     slot_precision = 0.9000999000999002\n","09/11/2024 19:08:47 - INFO - trainer -     slot_recall = 0.9385416666666667\n","mean_intent_slot increased (0.856670 --> 0.877827).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.53it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:09:08 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:09:08 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:09:08 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.04it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.40it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.60it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.68it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.66it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.08it/s]\n","09/11/2024 19:09:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:09:10 - INFO - trainer -     intent_acc = 0.7678571428571429\n","09/11/2024 19:09:10 - INFO - trainer -     loss = 1.9562516531773977\n","09/11/2024 19:09:10 - INFO - trainer -     mean_intent_slot = 0.8464157245632066\n","09/11/2024 19:09:10 - INFO - trainer -     semantic_frame_acc = 0.6045918367346939\n","09/11/2024 19:09:10 - INFO - trainer -     slot_f1 = 0.9249743062692702\n","09/11/2024 19:09:10 - INFO - trainer -     slot_precision = 0.9127789046653144\n","09/11/2024 19:09:10 - INFO - trainer -     slot_recall = 0.9375\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:09:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:09:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:09:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.94it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.77it/s]\n","09/11/2024 19:09:31 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:09:31 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 19:09:31 - INFO - trainer -     loss = 1.5784279916967665\n","09/11/2024 19:09:31 - INFO - trainer -     mean_intent_slot = 0.8810839083834973\n","09/11/2024 19:09:31 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 19:09:31 - INFO - trainer -     slot_f1 = 0.9177800616649537\n","09/11/2024 19:09:31 - INFO - trainer -     slot_precision = 0.9056795131845842\n","09/11/2024 19:09:31 - INFO - trainer -     slot_recall = 0.9302083333333333\n","mean_intent_slot increased (0.877827 --> 0.881084).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.46it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:09:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:09:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:09:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.89it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.37it/s]\n","09/11/2024 19:09:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:09:53 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 19:09:53 - INFO - trainer -     loss = 1.3000178496752466\n","09/11/2024 19:09:53 - INFO - trainer -     mean_intent_slot = 0.8893433860869748\n","09/11/2024 19:09:53 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 19:09:53 - INFO - trainer -     slot_f1 = 0.9342990170719089\n","09/11/2024 19:09:53 - INFO - trainer -     slot_precision = 0.9280575539568345\n","09/11/2024 19:09:53 - INFO - trainer -     slot_recall = 0.940625\n","mean_intent_slot increased (0.881084 --> 0.889343).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.38it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:10:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:10:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:10:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 19:10:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:10:16 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 19:10:16 - INFO - trainer -     loss = 1.2510984225996904\n","09/11/2024 19:10:16 - INFO - trainer -     mean_intent_slot = 0.8892988300718745\n","09/11/2024 19:10:16 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 19:10:16 - INFO - trainer -     slot_f1 = 0.9367609254498714\n","09/11/2024 19:10:16 - INFO - trainer -     slot_precision = 0.9248730964467005\n","09/11/2024 19:10:16 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:18<00:00,  2.93it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:10:36 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:10:36 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:10:36 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.80it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.84it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.26it/s]\n","09/11/2024 19:10:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:10:37 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:10:37 - INFO - trainer -     loss = 1.2490994110703468\n","09/11/2024 19:10:37 - INFO - trainer -     mean_intent_slot = 0.885500216778669\n","09/11/2024 19:10:37 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 19:10:37 - INFO - trainer -     slot_f1 = 0.9317147192716236\n","09/11/2024 19:10:37 - INFO - trainer -     slot_precision = 0.9056047197640118\n","09/11/2024 19:10:37 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.67it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:10:56 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:10:56 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:10:56 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:10:58 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:10:58 - INFO - trainer -     intent_acc = 0.8443877551020408\n","09/11/2024 19:10:58 - INFO - trainer -     loss = 1.2513449873243059\n","09/11/2024 19:10:58 - INFO - trainer -     mean_intent_slot = 0.8943451294672187\n","09/11/2024 19:10:58 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 19:10:58 - INFO - trainer -     slot_f1 = 0.9443025038323966\n","09/11/2024 19:10:58 - INFO - trainer -     slot_precision = 0.9267803410230692\n","09/11/2024 19:10:58 - INFO - trainer -     slot_recall = 0.9625\n","mean_intent_slot increased (0.889343 --> 0.894345).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.31it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:11:20 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:11:20 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:11:20 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:11:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:11:22 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:11:22 - INFO - trainer -     loss = 1.2850372229835816\n","09/11/2024 19:11:22 - INFO - trainer -     mean_intent_slot = 0.8903467813860764\n","09/11/2024 19:11:22 - INFO - trainer -     semantic_frame_acc = 0.701530612244898\n","09/11/2024 19:11:22 - INFO - trainer -     slot_f1 = 0.9439588688946016\n","09/11/2024 19:11:22 - INFO - trainer -     slot_precision = 0.9319796954314721\n","09/11/2024 19:11:22 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:11:40 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:11:40 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:11:40 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 19:11:42 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:11:42 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:11:42 - INFO - trainer -     loss = 1.3367047464208943\n","09/11/2024 19:11:42 - INFO - trainer -     mean_intent_slot = 0.888527760563824\n","09/11/2024 19:11:42 - INFO - trainer -     semantic_frame_acc = 0.6989795918367347\n","09/11/2024 19:11:42 - INFO - trainer -     slot_f1 = 0.9428718476582604\n","09/11/2024 19:11:42 - INFO - trainer -     slot_precision = 0.9318413021363174\n","09/11/2024 19:11:42 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:12:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:12:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:12:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.40it/s]\n","09/11/2024 19:12:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:12:03 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:12:03 - INFO - trainer -     loss = 1.2541641018220357\n","09/11/2024 19:12:03 - INFO - trainer -     mean_intent_slot = 0.8878075112941941\n","09/11/2024 19:12:03 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:12:03 - INFO - trainer -     slot_f1 = 0.9388803287108372\n","09/11/2024 19:12:03 - INFO - trainer -     slot_precision = 0.9260385005065856\n","09/11/2024 19:12:03 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:12:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:12:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:12:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.93it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 19:12:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:12:23 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 19:12:23 - INFO - trainer -     loss = 1.4260586742311716\n","09/11/2024 19:12:23 - INFO - trainer -     mean_intent_slot = 0.8817333856619571\n","09/11/2024 19:12:23 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 19:12:23 - INFO - trainer -     slot_f1 = 0.9394871794871794\n","09/11/2024 19:12:23 - INFO - trainer -     slot_precision = 0.9252525252525252\n","09/11/2024 19:12:23 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:18<00:00,  2.93it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:12:41 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:12:41 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:12:41 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.76it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.23it/s]\n","09/11/2024 19:12:43 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:12:43 - INFO - trainer -     intent_acc = 0.7908163265306123\n","09/11/2024 19:12:43 - INFO - trainer -     loss = 1.4523317541128822\n","09/11/2024 19:12:43 - INFO - trainer -     mean_intent_slot = 0.8606322745481501\n","09/11/2024 19:12:43 - INFO - trainer -     semantic_frame_acc = 0.6428571428571429\n","09/11/2024 19:12:43 - INFO - trainer -     slot_f1 = 0.9304482225656878\n","09/11/2024 19:12:43 - INFO - trainer -     slot_precision = 0.9204892966360856\n","09/11/2024 19:12:43 - INFO - trainer -     slot_recall = 0.940625\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:13:02 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:13:02 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:13:02 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:13:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:13:03 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:13:03 - INFO - trainer -     loss = 1.3948039741122298\n","09/11/2024 19:13:03 - INFO - trainer -     mean_intent_slot = 0.8846510540364446\n","09/11/2024 19:13:03 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:13:03 - INFO - trainer -     slot_f1 = 0.9351184346035015\n","09/11/2024 19:13:03 - INFO - trainer -     slot_precision = 0.924643584521385\n","09/11/2024 19:13:03 - INFO - trainer -     slot_recall = 0.9458333333333333\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:13:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:13:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:13:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.94it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.97it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.44it/s]\n","09/11/2024 19:13:24 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:13:24 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:13:24 - INFO - trainer -     loss = 1.473223660673414\n","09/11/2024 19:13:24 - INFO - trainer -     mean_intent_slot = 0.8772486000020857\n","09/11/2024 19:13:24 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:13:24 - INFO - trainer -     slot_f1 = 0.9381706693919265\n","09/11/2024 19:13:24 - INFO - trainer -     slot_precision = 0.9207622868605817\n","09/11/2024 19:13:24 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:13:42 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:13:42 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:13:42 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.30it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 19:13:44 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:13:44 - INFO - trainer -     intent_acc = 0.8137755102040817\n","09/11/2024 19:13:44 - INFO - trainer -     loss = 1.4045932295599155\n","09/11/2024 19:13:44 - INFO - trainer -     mean_intent_slot = 0.8791670158823284\n","09/11/2024 19:13:44 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:13:44 - INFO - trainer -     slot_f1 = 0.944558521560575\n","09/11/2024 19:13:44 - INFO - trainer -     slot_precision = 0.9311740890688259\n","09/11/2024 19:13:44 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:14:03 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:14:03 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:14:03 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 19:14:04 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:14:04 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:14:04 - INFO - trainer -     loss = 1.2644871867128782\n","09/11/2024 19:14:04 - INFO - trainer -     mean_intent_slot = 0.8922135007849293\n","09/11/2024 19:14:04 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:14:04 - INFO - trainer -     slot_f1 = 0.9476923076923076\n","09/11/2024 19:14:04 - INFO - trainer -     slot_precision = 0.9333333333333333\n","09/11/2024 19:14:04 - INFO - trainer -     slot_recall = 0.9625\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:18<00:00,  2.79it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:14:23 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:14:23 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:14:23 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.23it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.73it/s]\n","09/11/2024 19:14:25 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:14:25 - INFO - trainer -     intent_acc = 0.8112244897959183\n","09/11/2024 19:14:25 - INFO - trainer -     loss = 1.6973331512085028\n","09/11/2024 19:14:25 - INFO - trainer -     mean_intent_slot = 0.8795140536834889\n","09/11/2024 19:14:25 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:14:25 - INFO - trainer -     slot_f1 = 0.9478036175710595\n","09/11/2024 19:14:25 - INFO - trainer -     slot_precision = 0.9405128205128205\n","09/11/2024 19:14:25 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:14:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:14:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:14:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.34it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.37it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.37it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:14:45 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:14:45 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:14:45 - INFO - trainer -     loss = 1.6054141047144574\n","09/11/2024 19:14:45 - INFO - trainer -     mean_intent_slot = 0.8815615376585417\n","09/11/2024 19:14:45 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:14:45 - INFO - trainer -     slot_f1 = 0.9442455242966753\n","09/11/2024 19:14:45 - INFO - trainer -     slot_precision = 0.9276381909547738\n","09/11/2024 19:14:45 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:18<00:00,  2.83it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:15:04 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:15:04 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:15:04 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  4.02it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.18it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.59it/s]\n","09/11/2024 19:15:05 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:15:05 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:15:05 - INFO - trainer -     loss = 1.4199609133814062\n","09/11/2024 19:15:05 - INFO - trainer -     mean_intent_slot = 0.8869223309158374\n","09/11/2024 19:15:05 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 19:15:05 - INFO - trainer -     slot_f1 = 0.9473140495867768\n","09/11/2024 19:15:05 - INFO - trainer -     slot_precision = 0.9395491803278688\n","09/11/2024 19:15:05 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:15:24 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:15:24 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:15:24 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.16it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.77it/s]\n","09/11/2024 19:15:26 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:15:26 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 19:15:26 - INFO - trainer -     loss = 1.4554778723312276\n","09/11/2024 19:15:26 - INFO - trainer -     mean_intent_slot = 0.8847235497389898\n","09/11/2024 19:15:26 - INFO - trainer -     semantic_frame_acc = 0.7117346938775511\n","09/11/2024 19:15:26 - INFO - trainer -     slot_f1 = 0.9480185280494082\n","09/11/2024 19:15:26 - INFO - trainer -     slot_precision = 0.9369277721261444\n","09/11/2024 19:15:26 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:15:44 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:15:44 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:15:44 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.80it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.94it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.88it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.90it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.83it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.27it/s]\n","09/11/2024 19:15:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:15:46 - INFO - trainer -     intent_acc = 0.8290816326530612\n","09/11/2024 19:15:46 - INFO - trainer -     loss = 1.467089154225375\n","09/11/2024 19:15:46 - INFO - trainer -     mean_intent_slot = 0.8873891769822684\n","09/11/2024 19:15:46 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 19:15:46 - INFO - trainer -     slot_f1 = 0.9456967213114754\n","09/11/2024 19:15:46 - INFO - trainer -     slot_precision = 0.9304435483870968\n","09/11/2024 19:15:46 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:16:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:16:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:16:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:16:06 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:16:06 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 19:16:06 - INFO - trainer -     loss = 1.4711315422318876\n","09/11/2024 19:16:06 - INFO - trainer -     mean_intent_slot = 0.8851080754882599\n","09/11/2024 19:16:06 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:16:06 - INFO - trainer -     slot_f1 = 0.946236559139785\n","09/11/2024 19:16:06 - INFO - trainer -     slot_precision = 0.9305135951661632\n","09/11/2024 19:16:06 - INFO - trainer -     slot_recall = 0.9625\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:16:25 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:16:25 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:16:25 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.52it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.61it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.89it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.21it/s]\n","09/11/2024 19:16:27 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:16:27 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 19:16:27 - INFO - trainer -     loss = 1.5770137934014201\n","09/11/2024 19:16:27 - INFO - trainer -     mean_intent_slot = 0.8778564151080708\n","09/11/2024 19:16:27 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 19:16:27 - INFO - trainer -     slot_f1 = 0.93428425878757\n","09/11/2024 19:16:27 - INFO - trainer -     slot_precision = 0.9142572283150548\n","09/11/2024 19:16:27 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 16 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:16:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:16:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:16:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:16:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:16:47 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:16:47 - INFO - trainer -     loss = 1.5620545300522022\n","09/11/2024 19:16:47 - INFO - trainer -     mean_intent_slot = 0.8843057981778052\n","09/11/2024 19:16:47 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:16:47 - INFO - trainer -     slot_f1 = 0.9420809841107124\n","09/11/2024 19:16:47 - INFO - trainer -     slot_precision = 0.9273461150353178\n","09/11/2024 19:16:47 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 17 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:17:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:17:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:17:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:17:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:17:07 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:17:07 - INFO - trainer -     loss = 1.5610715024439352\n","09/11/2024 19:17:07 - INFO - trainer -     mean_intent_slot = 0.881600341873215\n","09/11/2024 19:17:07 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 19:17:07 - INFO - trainer -     slot_f1 = 0.9366700715015321\n","09/11/2024 19:17:07 - INFO - trainer -     slot_precision = 0.9188376753507014\n","09/11/2024 19:17:07 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 18 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:18<00:00,  2.86it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:17:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:17:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:17:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:17:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:17:28 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 19:17:28 - INFO - trainer -     loss = 1.5479788569999593\n","09/11/2024 19:17:28 - INFO - trainer -     mean_intent_slot = 0.8781668741304824\n","09/11/2024 19:17:28 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:17:28 - INFO - trainer -     slot_f1 = 0.9349051768323936\n","09/11/2024 19:17:28 - INFO - trainer -     slot_precision = 0.9202825428859738\n","09/11/2024 19:17:28 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 19 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:17:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:17:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:17:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:17:48 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:17:48 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:17:48 - INFO - trainer -     loss = 1.6279221795432801\n","09/11/2024 19:17:48 - INFO - trainer -     mean_intent_slot = 0.8768244971332138\n","09/11/2024 19:17:48 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:17:48 - INFO - trainer -     slot_f1 = 0.9347714432460195\n","09/11/2024 19:17:48 - INFO - trainer -     slot_precision = 0.9219858156028369\n","09/11/2024 19:17:48 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 20 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:18:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:18:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:18:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.90it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.42it/s]\n","09/11/2024 19:18:08 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:18:08 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:18:08 - INFO - trainer -     loss = 1.654954319320885\n","09/11/2024 19:18:08 - INFO - trainer -     mean_intent_slot = 0.8737420516396257\n","09/11/2024 19:18:08 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:18:08 - INFO - trainer -     slot_f1 = 0.9311575726670066\n","09/11/2024 19:18:08 - INFO - trainer -     slot_precision = 0.9120879120879121\n","09/11/2024 19:18:08 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 21 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:18:27 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:18:27 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:18:27 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.30it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:18:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:18:28 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:18:28 - INFO - trainer -     loss = 1.6218663201600845\n","09/11/2024 19:18:28 - INFO - trainer -     mean_intent_slot = 0.8759349391930685\n","09/11/2024 19:18:28 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:18:28 - INFO - trainer -     slot_f1 = 0.9329923273657289\n","09/11/2024 19:18:28 - INFO - trainer -     slot_precision = 0.9165829145728643\n","09/11/2024 19:18:28 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 22 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:18:47 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:18:47 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:18:47 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.03it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  3.98it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.99it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.52it/s]\n","09/11/2024 19:18:49 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:18:49 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:18:49 - INFO - trainer -     loss = 1.6295841901696153\n","09/11/2024 19:18:49 - INFO - trainer -     mean_intent_slot = 0.8759349391930685\n","09/11/2024 19:18:49 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:18:49 - INFO - trainer -     slot_f1 = 0.9329923273657289\n","09/11/2024 19:18:49 - INFO - trainer -     slot_precision = 0.9165829145728643\n","09/11/2024 19:18:49 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 23 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:19:08 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:19:08 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:19:08 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.34it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 19:19:09 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:19:09 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:19:09 - INFO - trainer -     loss = 1.6191603243350983\n","09/11/2024 19:19:09 - INFO - trainer -     mean_intent_slot = 0.8769579570958819\n","09/11/2024 19:19:09 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:19:09 - INFO - trainer -     slot_f1 = 0.9350383631713555\n","09/11/2024 19:19:09 - INFO - trainer -     slot_precision = 0.9185929648241206\n","09/11/2024 19:19:09 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 24 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:19:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:19:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:19:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.38it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.92it/s]\n","09/11/2024 19:19:29 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:19:29 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:19:29 - INFO - trainer -     loss = 1.5706158917995967\n","09/11/2024 19:19:29 - INFO - trainer -     mean_intent_slot = 0.8792674964722731\n","09/11/2024 19:19:29 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:19:29 - INFO - trainer -     slot_f1 = 0.9422084623323013\n","09/11/2024 19:19:29 - INFO - trainer -     slot_precision = 0.9335378323108384\n","09/11/2024 19:19:29 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 25 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:19:48 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:19:48 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:19:48 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:19:49 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:19:49 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:19:49 - INFO - trainer -     loss = 1.570521744666621\n","09/11/2024 19:19:49 - INFO - trainer -     mean_intent_slot = 0.8808436776772565\n","09/11/2024 19:19:49 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 19:19:49 - INFO - trainer -     slot_f1 = 0.945360824742268\n","09/11/2024 19:19:49 - INFO - trainer -     slot_precision = 0.9357142857142857\n","09/11/2024 19:19:49 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 26 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:20:08 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:20:08 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:20:08 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:20:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:20:10 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:20:10 - INFO - trainer -     loss = 1.6035709342852766\n","09/11/2024 19:20:10 - INFO - trainer -     mean_intent_slot = 0.8805385197557284\n","09/11/2024 19:20:10 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:20:10 - INFO - trainer -     slot_f1 = 0.9421994884910486\n","09/11/2024 19:20:10 - INFO - trainer -     slot_precision = 0.9256281407035176\n","09/11/2024 19:20:10 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 27 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:20:28 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:20:28 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:20:28 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.78it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.64it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.62it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.87it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.40it/s]\n","09/11/2024 19:20:30 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:20:30 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:20:30 - INFO - trainer -     loss = 1.5969268895153488\n","09/11/2024 19:20:30 - INFO - trainer -     mean_intent_slot = 0.8812625460020074\n","09/11/2024 19:20:30 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 19:20:30 - INFO - trainer -     slot_f1 = 0.9436475409836066\n","09/11/2024 19:20:30 - INFO - trainer -     slot_precision = 0.9284274193548387\n","09/11/2024 19:20:30 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 28 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:20:49 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:20:49 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:20:49 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.28it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 19:20:50 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:20:50 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:20:50 - INFO - trainer -     loss = 1.6211940017196216\n","09/11/2024 19:20:50 - INFO - trainer -     mean_intent_slot = 0.8782399916488335\n","09/11/2024 19:20:50 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 19:20:50 - INFO - trainer -     slot_f1 = 0.940153452685422\n","09/11/2024 19:20:50 - INFO - trainer -     slot_precision = 0.9236180904522613\n","09/11/2024 19:20:50 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 29 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:18<00:00,  2.97it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:21:09 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:21:09 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:21:09 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.83it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.77it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.25it/s]\n","09/11/2024 19:21:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:21:10 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:21:10 - INFO - trainer -     loss = 1.6365326858524765\n","09/11/2024 19:21:10 - INFO - trainer -     mean_intent_slot = 0.8790661364086216\n","09/11/2024 19:21:10 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:21:10 - INFO - trainer -     slot_f1 = 0.9392547217968352\n","09/11/2024 19:21:10 - INFO - trainer -     slot_precision = 0.9209209209209209\n","09/11/2024 19:21:10 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 30 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:21:29 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:21:29 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:21:29 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:21:31 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:21:31 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:21:31 - INFO - trainer -     loss = 1.6244566015167428\n","09/11/2024 19:21:31 - INFO - trainer -     mean_intent_slot = 0.87875150060024\n","09/11/2024 19:21:31 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 19:21:31 - INFO - trainer -     slot_f1 = 0.9411764705882352\n","09/11/2024 19:21:31 - INFO - trainer -     slot_precision = 0.9246231155778895\n","09/11/2024 19:21:31 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 31 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:21:49 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:21:49 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:21:49 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.00it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.04it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.53it/s]\n","09/11/2024 19:21:51 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:21:51 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:21:51 - INFO - trainer -     loss = 1.6110140520281024\n","09/11/2024 19:21:51 - INFO - trainer -     mean_intent_slot = 0.8799581371009944\n","09/11/2024 19:21:51 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 19:21:51 - INFO - trainer -     slot_f1 = 0.9435897435897437\n","09/11/2024 19:21:51 - INFO - trainer -     slot_precision = 0.9292929292929293\n","09/11/2024 19:21:51 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 32 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:22:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:22:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:22:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:22:11 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:22:11 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:22:11 - INFO - trainer -     loss = 1.633868353973542\n","09/11/2024 19:22:11 - INFO - trainer -     mean_intent_slot = 0.8791823652537938\n","09/11/2024 19:22:11 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:22:11 - INFO - trainer -     slot_f1 = 0.9394871794871794\n","09/11/2024 19:22:11 - INFO - trainer -     slot_precision = 0.9252525252525252\n","09/11/2024 19:22:11 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 33 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:22:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:22:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:22:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 19:22:31 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:22:31 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:22:31 - INFO - trainer -     loss = 1.6505919310397335\n","09/11/2024 19:22:31 - INFO - trainer -     mean_intent_slot = 0.8792334137956258\n","09/11/2024 19:22:31 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 19:22:31 - INFO - trainer -     slot_f1 = 0.9421402969790067\n","09/11/2024 19:22:31 - INFO - trainer -     slot_precision = 0.9264853977844915\n","09/11/2024 19:22:31 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 34 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:18<00:00,  2.83it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:22:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:22:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:22:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:22:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:22:52 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:22:52 - INFO - trainer -     loss = 1.660500244004652\n","09/11/2024 19:22:52 - INFO - trainer -     mean_intent_slot = 0.8784805631566854\n","09/11/2024 19:22:52 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:22:52 - INFO - trainer -     slot_f1 = 0.9406345957011258\n","09/11/2024 19:22:52 - INFO - trainer -     slot_precision = 0.9245472837022133\n","09/11/2024 19:22:52 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 35 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:18<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:23:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:23:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:23:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:23:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:23:12 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:23:12 - INFO - trainer -     loss = 1.664870371975537\n","09/11/2024 19:23:12 - INFO - trainer -     mean_intent_slot = 0.8794848584595129\n","09/11/2024 19:23:12 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 19:23:12 - INFO - trainer -     slot_f1 = 0.9400921658986175\n","09/11/2024 19:23:12 - INFO - trainer -     slot_precision = 0.9244712990936556\n","09/11/2024 19:23:12 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 36 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:18<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:23:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:23:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:23:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.52it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.62it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.69it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.68it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.29it/s]\n","09/11/2024 19:23:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:23:32 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:23:32 - INFO - trainer -     loss = 1.7059461444815887\n","09/11/2024 19:23:32 - INFO - trainer -     mean_intent_slot = 0.8789728256894156\n","09/11/2024 19:23:32 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 19:23:32 - INFO - trainer -     slot_f1 = 0.939068100358423\n","09/11/2024 19:23:32 - INFO - trainer -     slot_precision = 0.9234642497482377\n","09/11/2024 19:23:32 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 37 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:23:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:23:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:23:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.35it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.91it/s]\n","09/11/2024 19:23:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:23:52 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:23:52 - INFO - trainer -     loss = 1.675697365875489\n","09/11/2024 19:23:52 - INFO - trainer -     mean_intent_slot = 0.876718939109386\n","09/11/2024 19:23:52 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:23:52 - INFO - trainer -     slot_f1 = 0.9345603271983639\n","09/11/2024 19:23:52 - INFO - trainer -     slot_precision = 0.9176706827309237\n","09/11/2024 19:23:52 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 38 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:24:11 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:24:11 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:24:11 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.78it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.24it/s]\n","09/11/2024 19:24:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:24:12 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:24:12 - INFO - trainer -     loss = 1.675034058978781\n","09/11/2024 19:24:12 - INFO - trainer -     mean_intent_slot = 0.8777738112609701\n","09/11/2024 19:24:12 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:24:12 - INFO - trainer -     slot_f1 = 0.9366700715015321\n","09/11/2024 19:24:12 - INFO - trainer -     slot_precision = 0.9188376753507014\n","09/11/2024 19:24:12 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 39 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:24:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:24:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:24:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 19:24:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:24:33 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:24:33 - INFO - trainer -     loss = 1.6878734731581062\n","09/11/2024 19:24:33 - INFO - trainer -     mean_intent_slot = 0.8777738112609701\n","09/11/2024 19:24:33 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:24:33 - INFO - trainer -     slot_f1 = 0.9366700715015321\n","09/11/2024 19:24:33 - INFO - trainer -     slot_precision = 0.9188376753507014\n","09/11/2024 19:24:33 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 40 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:24:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:24:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:24:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.11it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.05it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.56it/s]\n","09/11/2024 19:24:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:24:53 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:24:53 - INFO - trainer -     loss = 1.6694808624950903\n","09/11/2024 19:24:53 - INFO - trainer -     mean_intent_slot = 0.8784924839501018\n","09/11/2024 19:24:53 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:24:53 - INFO - trainer -     slot_f1 = 0.9381074168797954\n","09/11/2024 19:24:53 - INFO - trainer -     slot_precision = 0.9216080402010051\n","09/11/2024 19:24:53 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 41 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:25:11 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:25:11 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:25:11 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.30it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 19:25:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:25:13 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:25:13 - INFO - trainer -     loss = 1.6710928761001145\n","09/11/2024 19:25:13 - INFO - trainer -     mean_intent_slot = 0.8784924839501018\n","09/11/2024 19:25:13 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:25:13 - INFO - trainer -     slot_f1 = 0.9381074168797954\n","09/11/2024 19:25:13 - INFO - trainer -     slot_precision = 0.9216080402010051\n","09/11/2024 19:25:13 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 42 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Epoch: 100% 50/50 [17:07<00:00, 20.55s/it]\n","09/11/2024 19:25:13 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 19:25:13 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 19:25:13 - INFO - trainer -     Num examples = 346\n","09/11/2024 19:25:13 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.75it/s]\n","09/11/2024 19:25:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:25:15 - INFO - trainer -     intent_acc = 0.8526011560693642\n","09/11/2024 19:25:15 - INFO - trainer -     loss = 1.3575103481610615\n","09/11/2024 19:25:15 - INFO - trainer -     mean_intent_slot = 0.8857254981624776\n","09/11/2024 19:25:15 - INFO - trainer -     semantic_frame_acc = 0.6589595375722543\n","09/11/2024 19:25:15 - INFO - trainer -     slot_f1 = 0.918849840255591\n","09/11/2024 19:25:15 - INFO - trainer -     slot_precision = 0.9089759797724399\n","09/11/2024 19:25:15 - INFO - trainer -     slot_recall = 0.9289405684754521\n"]}]},{"cell_type":"code","source":["# First, run the previous bash script to train JointBERT-CRF_PhoBERTencoder\n","# !bash run_jointBERT-CRF_PhoBERTencoder.sh\n","\n","# Now set up environment variables for the new training run\n","lr = \"4e-5\"\n","c = \"0.4\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Set the MODEL_DIR path for JointIDSF\n","MODEL_DIR = f\"Model_Hackathon/JointIDSF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Run the second python script using the pretrained model path\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_intent_context_attention \\\n","                  --attention_embedding_size 200 \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --pretrained \\\n","                  --pretrained_path Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Uq9v3N_yjWUl","executionInfo":{"status":"ok","timestamp":1726083858303,"user_tz":-420,"elapsed":1037768,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"2f437efe-3833-4e5d-9bb8-0748a966d9ca"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["4e-5\n","Model_Hackathon/JointIDSF_CLPhoBERTencoder/4e-5/0.4/100\n","2024-09-11 19:27:13.407291: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 19:27:13.429080: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 19:27:13.435178: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 19:27:13.450411: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 19:27:14.749716: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","09/11/2024 19:27:16 - INFO - data_loader -   Loading features from cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","/content/ViNLU/data_loader.py:238: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n","  features = torch.load(cached_features_file)\n","09/11/2024 19:27:16 - INFO - data_loader -   Loading features from cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 19:27:16 - INFO - data_loader -   Loading features from cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","phongtintruong/clphobert-base-16-256-50-30\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 and are newly initialized: ['slot_classifier.attention.linear_out.weight', 'slot_classifier.linear_intent_context.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 19:27:16 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:27:16 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:27:16 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:02<00:00,  3.16it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 19:27:19 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:27:19 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 19:27:19 - INFO - trainer -     loss = 23.407176562717982\n","09/11/2024 19:27:19 - INFO - trainer -     mean_intent_slot = 0.4339380645369787\n","09/11/2024 19:27:19 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 19:27:19 - INFO - trainer -     slot_f1 = 0.015835312747426764\n","09/11/2024 19:27:19 - INFO - trainer -     slot_precision = 0.010604453870625663\n","09/11/2024 19:27:19 - INFO - trainer -     slot_recall = 0.03125\n","{'loss': 23.407176562717982, 'intent_acc': 0.8520408163265306, 'slot_precision': 0.010604453870625663, 'slot_recall': 0.03125, 'slot_f1': 0.015835312747426764, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.4339380645369787}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 19:27:19 - INFO - trainer -   ***** Running training *****\n","09/11/2024 19:27:19 - INFO - trainer -     Num examples = 1790\n","09/11/2024 19:27:19 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 19:27:19 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 19:27:19 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 19:27:19 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 19:27:19 - INFO - trainer -     Logging steps = 56\n","09/11/2024 19:27:19 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:17<00:00,  3.15it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:27:37 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:27:37 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:27:37 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.06it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.05it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.10it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.53it/s]\n","09/11/2024 19:27:38 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:27:38 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 19:27:38 - INFO - trainer -     loss = 7.987322977610996\n","09/11/2024 19:27:38 - INFO - trainer -     mean_intent_slot = 0.8563621626497713\n","09/11/2024 19:27:38 - INFO - trainer -     semantic_frame_acc = 0.32142857142857145\n","09/11/2024 19:27:38 - INFO - trainer -     slot_f1 = 0.8632345293811753\n","09/11/2024 19:27:38 - INFO - trainer -     slot_precision = 0.8618899273104881\n","09/11/2024 19:27:38 - INFO - trainer -     slot_recall = 0.8645833333333334\n","mean_intent_slot increased (inf --> 0.856362).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.52it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:17<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:27:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:27:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:27:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:28:01 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:28:01 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 19:28:01 - INFO - trainer -     loss = 3.6235237547329495\n","09/11/2024 19:28:01 - INFO - trainer -     mean_intent_slot = 0.8662115660099238\n","09/11/2024 19:28:01 - INFO - trainer -     semantic_frame_acc = 0.5790816326530612\n","09/11/2024 19:28:01 - INFO - trainer -     slot_f1 = 0.9084435401831128\n","09/11/2024 19:28:01 - INFO - trainer -     slot_precision = 0.8876739562624254\n","09/11/2024 19:28:01 - INFO - trainer -     slot_recall = 0.9302083333333333\n","mean_intent_slot increased (0.856362 --> 0.866212).  Saving model ...\n","Iteration: 100% 56/56 [00:21<00:00,  2.56it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:18<00:00,  2.85it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:28:22 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:28:22 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:28:22 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.03it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.12it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.14it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 19:28:24 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:28:24 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 19:28:24 - INFO - trainer -     loss = 2.1685445649283275\n","09/11/2024 19:28:24 - INFO - trainer -     mean_intent_slot = 0.8803351355856279\n","09/11/2024 19:28:24 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:28:24 - INFO - trainer -     slot_f1 = 0.9137314956610516\n","09/11/2024 19:28:24 - INFO - trainer -     slot_precision = 0.8958958958958959\n","09/11/2024 19:28:24 - INFO - trainer -     slot_recall = 0.9322916666666666\n","mean_intent_slot increased (0.866212 --> 0.880335).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.41it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:28:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:28:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:28:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.00it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.98it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.53it/s]\n","09/11/2024 19:28:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:28:47 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 19:28:47 - INFO - trainer -     loss = 1.8531470532928194\n","09/11/2024 19:28:47 - INFO - trainer -     mean_intent_slot = 0.88834840854256\n","09/11/2024 19:28:47 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:28:47 - INFO - trainer -     slot_f1 = 0.9272070211667527\n","09/11/2024 19:28:47 - INFO - trainer -     slot_precision = 0.9191402251791198\n","09/11/2024 19:28:47 - INFO - trainer -     slot_recall = 0.9354166666666667\n","mean_intent_slot increased (0.880335 --> 0.888348).  Saving model ...\n","Iteration: 100% 56/56 [00:24<00:00,  2.25it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:18<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:29:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:29:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:29:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:29:11 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:29:11 - INFO - trainer -     intent_acc = 0.7908163265306123\n","09/11/2024 19:29:11 - INFO - trainer -     loss = 1.6460074239543505\n","09/11/2024 19:29:11 - INFO - trainer -     mean_intent_slot = 0.8616243794815224\n","09/11/2024 19:29:11 - INFO - trainer -     semantic_frame_acc = 0.6403061224489796\n","09/11/2024 19:29:11 - INFO - trainer -     slot_f1 = 0.9324324324324325\n","09/11/2024 19:29:11 - INFO - trainer -     slot_precision = 0.9304979253112033\n","09/11/2024 19:29:11 - INFO - trainer -     slot_recall = 0.934375\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:18<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:29:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:29:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:29:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.55it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.74it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.29it/s]\n","09/11/2024 19:29:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:29:32 - INFO - trainer -     intent_acc = 0.7831632653061225\n","09/11/2024 19:29:32 - INFO - trainer -     loss = 1.6143793261476926\n","09/11/2024 19:29:32 - INFO - trainer -     mean_intent_slot = 0.8557014054976663\n","09/11/2024 19:29:32 - INFO - trainer -     semantic_frame_acc = 0.6301020408163265\n","09/11/2024 19:29:32 - INFO - trainer -     slot_f1 = 0.9282395456892101\n","09/11/2024 19:29:32 - INFO - trainer -     slot_precision = 0.9201637666325486\n","09/11/2024 19:29:32 - INFO - trainer -     slot_recall = 0.9364583333333333\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:29:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:29:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:29:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:29:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:29:52 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 19:29:52 - INFO - trainer -     loss = 1.3433358589453357\n","09/11/2024 19:29:52 - INFO - trainer -     mean_intent_slot = 0.873045831980817\n","09/11/2024 19:29:52 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:29:52 - INFO - trainer -     slot_f1 = 0.9399692149820421\n","09/11/2024 19:29:52 - INFO - trainer -     slot_precision = 0.9261880687563195\n","09/11/2024 19:29:52 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:30:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:30:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:30:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.83it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.93it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.98it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.85it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.33it/s]\n","09/11/2024 19:30:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:30:12 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 19:30:12 - INFO - trainer -     loss = 1.2787822932004929\n","09/11/2024 19:30:12 - INFO - trainer -     mean_intent_slot = 0.8781246071323807\n","09/11/2024 19:30:12 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:30:12 - INFO - trainer -     slot_f1 = 0.9373716632443532\n","09/11/2024 19:30:12 - INFO - trainer -     slot_precision = 0.9240890688259109\n","09/11/2024 19:30:12 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:30:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:30:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:30:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.24it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.91it/s]\n","09/11/2024 19:30:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:30:32 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:30:32 - INFO - trainer -     loss = 1.3929531438542264\n","09/11/2024 19:30:32 - INFO - trainer -     mean_intent_slot = 0.8672456347159803\n","09/11/2024 19:30:32 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:30:32 - INFO - trainer -     slot_f1 = 0.9334708612686952\n","09/11/2024 19:30:32 - INFO - trainer -     slot_precision = 0.9244126659856997\n","09/11/2024 19:30:32 - INFO - trainer -     slot_recall = 0.9427083333333334\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:18<00:00,  2.85it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:30:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:30:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:30:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.73it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.57it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.54it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.53it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.07it/s]\n","09/11/2024 19:30:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:30:53 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:30:53 - INFO - trainer -     loss = 1.4177923460624047\n","09/11/2024 19:30:53 - INFO - trainer -     mean_intent_slot = 0.8716406315612665\n","09/11/2024 19:30:53 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 19:30:53 - INFO - trainer -     slot_f1 = 0.926954732510288\n","09/11/2024 19:30:53 - INFO - trainer -     slot_precision = 0.915650406504065\n","09/11/2024 19:30:53 - INFO - trainer -     slot_recall = 0.9385416666666667\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:31:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:31:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:31:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:31:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:31:13 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:31:13 - INFO - trainer -     loss = 1.2822730791355883\n","09/11/2024 19:31:13 - INFO - trainer -     mean_intent_slot = 0.879939547025439\n","09/11/2024 19:31:13 - INFO - trainer -     semantic_frame_acc = 0.7066326530612245\n","09/11/2024 19:31:13 - INFO - trainer -     slot_f1 = 0.9435525634386329\n","09/11/2024 19:31:13 - INFO - trainer -     slot_precision = 0.9382080329557158\n","09/11/2024 19:31:13 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:31:32 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:31:32 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:31:32 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.30it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:31:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:31:33 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 19:31:33 - INFO - trainer -     loss = 1.3556134083441325\n","09/11/2024 19:31:33 - INFO - trainer -     mean_intent_slot = 0.8727496776830918\n","09/11/2024 19:31:33 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:31:33 - INFO - trainer -     slot_f1 = 0.9368258859784284\n","09/11/2024 19:31:33 - INFO - trainer -     slot_precision = 0.9240121580547113\n","09/11/2024 19:31:33 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:18<00:00,  2.95it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:31:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:31:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:31:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 19:31:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:31:53 - INFO - trainer -     intent_acc = 0.7755102040816326\n","09/11/2024 19:31:53 - INFO - trainer -     loss = 1.4965428320158805\n","09/11/2024 19:31:53 - INFO - trainer -     mean_intent_slot = 0.8581006409784131\n","09/11/2024 19:31:53 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:31:53 - INFO - trainer -     slot_f1 = 0.9406910778751935\n","09/11/2024 19:31:53 - INFO - trainer -     slot_precision = 0.9315628192032687\n","09/11/2024 19:31:53 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:18<00:00,  3.09it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:32:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:32:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:32:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.37it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.92it/s]\n","09/11/2024 19:32:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:32:13 - INFO - trainer -     intent_acc = 0.7729591836734694\n","09/11/2024 19:32:13 - INFO - trainer -     loss = 1.596439879254571\n","09/11/2024 19:32:13 - INFO - trainer -     mean_intent_slot = 0.8532150224710823\n","09/11/2024 19:32:13 - INFO - trainer -     semantic_frame_acc = 0.6326530612244898\n","09/11/2024 19:32:13 - INFO - trainer -     slot_f1 = 0.9334708612686952\n","09/11/2024 19:32:13 - INFO - trainer -     slot_precision = 0.9244126659856997\n","09/11/2024 19:32:13 - INFO - trainer -     slot_recall = 0.9427083333333334\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:18<00:00,  2.86it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:32:32 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:32:32 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:32:32 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  4.00it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.13it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.59it/s]\n","09/11/2024 19:32:34 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:32:34 - INFO - trainer -     intent_acc = 0.7959183673469388\n","09/11/2024 19:32:34 - INFO - trainer -     loss = 1.4582397316449456\n","09/11/2024 19:32:34 - INFO - trainer -     mean_intent_slot = 0.8691525993113295\n","09/11/2024 19:32:34 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:32:34 - INFO - trainer -     slot_f1 = 0.9423868312757202\n","09/11/2024 19:32:34 - INFO - trainer -     slot_precision = 0.9308943089430894\n","09/11/2024 19:32:34 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:32:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:32:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:32:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:32:54 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:32:54 - INFO - trainer -     intent_acc = 0.7882653061224489\n","09/11/2024 19:32:54 - INFO - trainer -     loss = 1.5441858699279172\n","09/11/2024 19:32:54 - INFO - trainer -     mean_intent_slot = 0.864419538307126\n","09/11/2024 19:32:54 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:32:54 - INFO - trainer -     slot_f1 = 0.9405737704918032\n","09/11/2024 19:32:54 - INFO - trainer -     slot_precision = 0.9254032258064516\n","09/11/2024 19:32:54 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:33:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:33:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:33:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.83it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.24it/s]\n","09/11/2024 19:33:14 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:33:14 - INFO - trainer -     intent_acc = 0.7959183673469388\n","09/11/2024 19:33:14 - INFO - trainer -     loss = 1.4073240737031614\n","09/11/2024 19:33:14 - INFO - trainer -     mean_intent_slot = 0.871561668145519\n","09/11/2024 19:33:14 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:33:14 - INFO - trainer -     slot_f1 = 0.9472049689440993\n","09/11/2024 19:33:14 - INFO - trainer -     slot_precision = 0.941358024691358\n","09/11/2024 19:33:14 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:33:33 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:33:33 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:33:33 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.31it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 19:33:34 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:33:34 - INFO - trainer -     intent_acc = 0.7908163265306123\n","09/11/2024 19:33:34 - INFO - trainer -     loss = 1.4632594624667294\n","09/11/2024 19:33:34 - INFO - trainer -     mean_intent_slot = 0.8643522626441882\n","09/11/2024 19:33:34 - INFO - trainer -     semantic_frame_acc = 0.6632653061224489\n","09/11/2024 19:33:34 - INFO - trainer -     slot_f1 = 0.9378881987577641\n","09/11/2024 19:33:34 - INFO - trainer -     slot_precision = 0.9320987654320988\n","09/11/2024 19:33:34 - INFO - trainer -     slot_recall = 0.94375\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:33:53 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:33:53 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:33:53 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.90it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.99it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.39it/s]\n","09/11/2024 19:33:54 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:33:54 - INFO - trainer -     intent_acc = 0.7806122448979592\n","09/11/2024 19:33:54 - INFO - trainer -     loss = 1.5650471208084906\n","09/11/2024 19:33:54 - INFO - trainer -     mean_intent_slot = 0.8617055095787038\n","09/11/2024 19:33:54 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 19:33:54 - INFO - trainer -     slot_f1 = 0.9427987742594484\n","09/11/2024 19:33:54 - INFO - trainer -     slot_precision = 0.9248496993987976\n","09/11/2024 19:33:54 - INFO - trainer -     slot_recall = 0.9614583333333333\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:34:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:34:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:34:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.28it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 19:34:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:34:15 - INFO - trainer -     intent_acc = 0.7780612244897959\n","09/11/2024 19:34:15 - INFO - trainer -     loss = 1.5534237161544817\n","09/11/2024 19:34:15 - INFO - trainer -     mean_intent_slot = 0.8594979979665209\n","09/11/2024 19:34:15 - INFO - trainer -     semantic_frame_acc = 0.6428571428571429\n","09/11/2024 19:34:15 - INFO - trainer -     slot_f1 = 0.9409347714432461\n","09/11/2024 19:34:15 - INFO - trainer -     slot_precision = 0.92806484295846\n","09/11/2024 19:34:15 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 16 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:34:33 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:34:33 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:34:33 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.97it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.41it/s]\n","09/11/2024 19:34:35 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:34:35 - INFO - trainer -     intent_acc = 0.7908163265306123\n","09/11/2024 19:34:35 - INFO - trainer -     loss = 1.540616259511028\n","09/11/2024 19:34:35 - INFO - trainer -     mean_intent_slot = 0.8649957921312854\n","09/11/2024 19:34:35 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:34:35 - INFO - trainer -     slot_f1 = 0.9391752577319586\n","09/11/2024 19:34:35 - INFO - trainer -     slot_precision = 0.9295918367346939\n","09/11/2024 19:34:35 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 17 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:34:53 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:34:53 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:34:53 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.23it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:34:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:34:55 - INFO - trainer -     intent_acc = 0.7780612244897959\n","09/11/2024 19:34:55 - INFO - trainer -     loss = 1.4030808810410755\n","09/11/2024 19:34:55 - INFO - trainer -     mean_intent_slot = 0.8642115843234914\n","09/11/2024 19:34:55 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:34:55 - INFO - trainer -     slot_f1 = 0.9503619441571871\n","09/11/2024 19:34:55 - INFO - trainer -     slot_precision = 0.9435318275154004\n","09/11/2024 19:34:55 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 18 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:35:14 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:35:14 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:35:14 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:35:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:35:15 - INFO - trainer -     intent_acc = 0.7729591836734694\n","09/11/2024 19:35:15 - INFO - trainer -     loss = 1.5365616574085184\n","09/11/2024 19:35:15 - INFO - trainer -     mean_intent_slot = 0.8547948932277702\n","09/11/2024 19:35:15 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:35:15 - INFO - trainer -     slot_f1 = 0.9366306027820711\n","09/11/2024 19:35:15 - INFO - trainer -     slot_precision = 0.926605504587156\n","09/11/2024 19:35:15 - INFO - trainer -     slot_recall = 0.946875\n","EarlyStopping counter: 19 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:18<00:00,  2.90it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:35:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:35:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:35:34 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.34it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.40it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.40it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.94it/s]\n","09/11/2024 19:35:35 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:35:35 - INFO - trainer -     intent_acc = 0.7806122448979592\n","09/11/2024 19:35:35 - INFO - trainer -     loss = 1.4956367478173758\n","09/11/2024 19:35:35 - INFO - trainer -     mean_intent_slot = 0.8617420462781098\n","09/11/2024 19:35:35 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:35:35 - INFO - trainer -     slot_f1 = 0.9428718476582604\n","09/11/2024 19:35:35 - INFO - trainer -     slot_precision = 0.9318413021363174\n","09/11/2024 19:35:35 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 20 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:35:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:35:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:35:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:35:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:35:55 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 19:35:55 - INFO - trainer -     loss = 1.4990560268051922\n","09/11/2024 19:35:55 - INFO - trainer -     mean_intent_slot = 0.8767454350161117\n","09/11/2024 19:35:55 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:35:55 - INFO - trainer -     slot_f1 = 0.9473684210526315\n","09/11/2024 19:35:55 - INFO - trainer -     slot_precision = 0.9386503067484663\n","09/11/2024 19:35:55 - INFO - trainer -     slot_recall = 0.95625\n","EarlyStopping counter: 21 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:36:14 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:36:14 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:36:14 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.68it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  4.02it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.08it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.57it/s]\n","09/11/2024 19:36:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:36:16 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:36:16 - INFO - trainer -     loss = 1.4744355075194366\n","09/11/2024 19:36:16 - INFO - trainer -     mean_intent_slot = 0.8715150175275093\n","09/11/2024 19:36:16 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:36:16 - INFO - trainer -     slot_f1 = 0.949662688116243\n","09/11/2024 19:36:16 - INFO - trainer -     slot_precision = 0.9462254395036195\n","09/11/2024 19:36:16 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 22 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:36:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:36:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:36:34 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:36:36 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:36:36 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:36:36 - INFO - trainer -     loss = 1.5106882995127566\n","09/11/2024 19:36:36 - INFO - trainer -     mean_intent_slot = 0.8689344442813096\n","09/11/2024 19:36:36 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:36:36 - INFO - trainer -     slot_f1 = 0.9445015416238438\n","09/11/2024 19:36:36 - INFO - trainer -     slot_precision = 0.9320486815415822\n","09/11/2024 19:36:36 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 23 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:36:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:36:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:36:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.71it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.74it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.23it/s]\n","09/11/2024 19:36:56 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:36:56 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:36:56 - INFO - trainer -     loss = 1.562938041851989\n","09/11/2024 19:36:56 - INFO - trainer -     mean_intent_slot = 0.868119597298518\n","09/11/2024 19:36:56 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:36:56 - INFO - trainer -     slot_f1 = 0.9428718476582604\n","09/11/2024 19:36:56 - INFO - trainer -     slot_precision = 0.9318413021363174\n","09/11/2024 19:36:56 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 24 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:37:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:37:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:37:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:37:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:37:16 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:37:16 - INFO - trainer -     loss = 1.5562385395169258\n","09/11/2024 19:37:16 - INFO - trainer -     mean_intent_slot = 0.8657558384178414\n","09/11/2024 19:37:16 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 19:37:16 - INFO - trainer -     slot_f1 = 0.9381443298969072\n","09/11/2024 19:37:16 - INFO - trainer -     slot_precision = 0.9285714285714286\n","09/11/2024 19:37:16 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 25 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:37:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:37:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:37:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.61it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.80it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.87it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.36it/s]\n","09/11/2024 19:37:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:37:37 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 19:37:37 - INFO - trainer -     loss = 1.6041561397723854\n","09/11/2024 19:37:37 - INFO - trainer -     mean_intent_slot = 0.8707122679580307\n","09/11/2024 19:37:37 - INFO - trainer -     semantic_frame_acc = 0.6505102040816326\n","09/11/2024 19:37:37 - INFO - trainer -     slot_f1 = 0.9378531073446328\n","09/11/2024 19:37:37 - INFO - trainer -     slot_precision = 0.9250253292806484\n","09/11/2024 19:37:37 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 26 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:37:55 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:37:55 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:37:55 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.34it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:37:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:37:57 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 19:37:57 - INFO - trainer -     loss = 1.4256329552403517\n","09/11/2024 19:37:57 - INFO - trainer -     mean_intent_slot = 0.8765285093944842\n","09/11/2024 19:37:57 - INFO - trainer -     semantic_frame_acc = 0.6811224489795918\n","09/11/2024 19:37:57 - INFO - trainer -     slot_f1 = 0.9469345698093766\n","09/11/2024 19:37:57 - INFO - trainer -     slot_precision = 0.9367991845056065\n","09/11/2024 19:37:57 - INFO - trainer -     slot_recall = 0.9572916666666667\n","EarlyStopping counter: 27 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:38:16 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:38:16 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:38:16 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.11it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.30it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 19:38:17 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:38:17 - INFO - trainer -     intent_acc = 0.7959183673469388\n","09/11/2024 19:38:17 - INFO - trainer -     loss = 1.404754419744547\n","09/11/2024 19:38:17 - INFO - trainer -     mean_intent_slot = 0.8724305606719223\n","09/11/2024 19:38:17 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:38:17 - INFO - trainer -     slot_f1 = 0.9489427539969056\n","09/11/2024 19:38:17 - INFO - trainer -     slot_precision = 0.9397344228804902\n","09/11/2024 19:38:17 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 28 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:18<00:00,  2.95it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:38:36 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:38:36 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:38:36 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.26it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:38:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:38:37 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:38:37 - INFO - trainer -     loss = 1.4776326059363782\n","09/11/2024 19:38:37 - INFO - trainer -     mean_intent_slot = 0.8704491055681531\n","09/11/2024 19:38:37 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:38:37 - INFO - trainer -     slot_f1 = 0.9475308641975307\n","09/11/2024 19:38:37 - INFO - trainer -     slot_precision = 0.9359756097560976\n","09/11/2024 19:38:37 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 29 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:38:56 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:38:56 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:38:56 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.20it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:38:58 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:38:58 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:38:58 - INFO - trainer -     loss = 1.4370465891302697\n","09/11/2024 19:38:58 - INFO - trainer -     mean_intent_slot = 0.8751478852410529\n","09/11/2024 19:38:58 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 19:38:58 - INFO - trainer -     slot_f1 = 0.9492753623188406\n","09/11/2024 19:38:58 - INFO - trainer -     slot_precision = 0.9434156378600823\n","09/11/2024 19:38:58 - INFO - trainer -     slot_recall = 0.9552083333333333\n","EarlyStopping counter: 30 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:39:17 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:39:17 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:39:17 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.88it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.36it/s]\n","09/11/2024 19:39:18 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:39:18 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 19:39:18 - INFO - trainer -     loss = 1.4826286604761012\n","09/11/2024 19:39:18 - INFO - trainer -     mean_intent_slot = 0.8742218006336109\n","09/11/2024 19:39:18 - INFO - trainer -     semantic_frame_acc = 0.6760204081632653\n","09/11/2024 19:39:18 - INFO - trainer -     slot_f1 = 0.9499742135121196\n","09/11/2024 19:39:18 - INFO - trainer -     slot_precision = 0.940755873340143\n","09/11/2024 19:39:18 - INFO - trainer -     slot_recall = 0.959375\n","EarlyStopping counter: 31 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.69it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:39:37 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:39:37 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:39:37 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.21it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.26it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:39:39 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:39:39 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 19:39:39 - INFO - trainer -     loss = 1.6058531496673822\n","09/11/2024 19:39:39 - INFO - trainer -     mean_intent_slot = 0.86991370622323\n","09/11/2024 19:39:39 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:39:39 - INFO - trainer -     slot_f1 = 0.9413580246913581\n","09/11/2024 19:39:39 - INFO - trainer -     slot_precision = 0.9298780487804879\n","09/11/2024 19:39:39 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 32 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:39:57 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:39:57 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:39:57 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.15it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.03it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.92it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.51it/s]\n","09/11/2024 19:39:59 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:39:59 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:39:59 - INFO - trainer -     loss = 1.651421362900042\n","09/11/2024 19:39:59 - INFO - trainer -     mean_intent_slot = 0.8684424770421252\n","09/11/2024 19:39:59 - INFO - trainer -     semantic_frame_acc = 0.6428571428571429\n","09/11/2024 19:39:59 - INFO - trainer -     slot_f1 = 0.9358645459209851\n","09/11/2024 19:39:59 - INFO - trainer -     slot_precision = 0.9221435793731041\n","09/11/2024 19:39:59 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 33 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:40:18 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:40:18 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:40:18 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.30it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 19:40:19 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:40:19 - INFO - trainer -     intent_acc = 0.7959183673469388\n","09/11/2024 19:40:19 - INFO - trainer -     loss = 1.601574874682618\n","09/11/2024 19:40:19 - INFO - trainer -     mean_intent_slot = 0.8690932042920261\n","09/11/2024 19:40:19 - INFO - trainer -     semantic_frame_acc = 0.6658163265306123\n","09/11/2024 19:40:19 - INFO - trainer -     slot_f1 = 0.9422680412371134\n","09/11/2024 19:40:19 - INFO - trainer -     slot_precision = 0.9326530612244898\n","09/11/2024 19:40:19 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 34 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:40:38 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:40:38 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:40:38 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:40:39 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:40:39 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:40:39 - INFO - trainer -     loss = 1.6569651611082787\n","09/11/2024 19:40:39 - INFO - trainer -     mean_intent_slot = 0.8683765279890876\n","09/11/2024 19:40:39 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:40:39 - INFO - trainer -     slot_f1 = 0.93573264781491\n","09/11/2024 19:40:39 - INFO - trainer -     slot_precision = 0.9238578680203046\n","09/11/2024 19:40:39 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 35 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:40:58 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:40:58 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:40:58 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:41:00 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:41:00 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:41:00 - INFO - trainer -     loss = 1.7152292088805032\n","09/11/2024 19:41:00 - INFO - trainer -     mean_intent_slot = 0.8671768707482993\n","09/11/2024 19:41:00 - INFO - trainer -     semantic_frame_acc = 0.6479591836734694\n","09/11/2024 19:41:00 - INFO - trainer -     slot_f1 = 0.9333333333333333\n","09/11/2024 19:41:00 - INFO - trainer -     slot_precision = 0.9191919191919192\n","09/11/2024 19:41:00 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 36 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:41:18 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:41:18 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:41:18 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.24it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 19:41:20 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:41:20 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:41:20 - INFO - trainer -     loss = 1.7007158329776888\n","09/11/2024 19:41:20 - INFO - trainer -     mean_intent_slot = 0.8669032261442289\n","09/11/2024 19:41:20 - INFO - trainer -     semantic_frame_acc = 0.6479591836734694\n","09/11/2024 19:41:20 - INFO - trainer -     slot_f1 = 0.9327860441251924\n","09/11/2024 19:41:20 - INFO - trainer -     slot_precision = 0.9191102123356926\n","09/11/2024 19:41:20 - INFO - trainer -     slot_recall = 0.946875\n","EarlyStopping counter: 37 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:41:38 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:41:38 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:41:38 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.18it/s]\n","09/11/2024 19:41:40 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:41:40 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:41:40 - INFO - trainer -     loss = 1.67225333782179\n","09/11/2024 19:41:40 - INFO - trainer -     mean_intent_slot = 0.8686499779768022\n","09/11/2024 19:41:40 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:41:40 - INFO - trainer -     slot_f1 = 0.9362795477903391\n","09/11/2024 19:41:40 - INFO - trainer -     slot_precision = 0.9239350912778904\n","09/11/2024 19:41:40 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 38 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:18<00:00,  3.00it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:41:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:41:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:41:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.22it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 19:42:00 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:42:00 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 19:42:00 - INFO - trainer -     loss = 1.687325072175424\n","09/11/2024 19:42:00 - INFO - trainer -     mean_intent_slot = 0.867134026183663\n","09/11/2024 19:42:00 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:42:00 - INFO - trainer -     slot_f1 = 0.9357986646122239\n","09/11/2024 19:42:00 - INFO - trainer -     slot_precision = 0.922998986828774\n","09/11/2024 19:42:00 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 39 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:42:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:42:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:42:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.81it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.71it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.13it/s]\n","09/11/2024 19:42:21 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:42:21 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:42:21 - INFO - trainer -     loss = 1.6867196226958185\n","09/11/2024 19:42:21 - INFO - trainer -     mean_intent_slot = 0.8689231470708468\n","09/11/2024 19:42:21 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:42:21 - INFO - trainer -     slot_f1 = 0.9368258859784284\n","09/11/2024 19:42:21 - INFO - trainer -     slot_precision = 0.9240121580547113\n","09/11/2024 19:42:21 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 40 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:42:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:42:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:42:39 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.18it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.26it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 19:42:41 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:42:41 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 19:42:41 - INFO - trainer -     loss = 1.6558585472937142\n","09/11/2024 19:42:41 - INFO - trainer -     mean_intent_slot = 0.8681292954199675\n","09/11/2024 19:42:41 - INFO - trainer -     semantic_frame_acc = 0.6530612244897959\n","09/11/2024 19:42:41 - INFO - trainer -     slot_f1 = 0.9377892030848329\n","09/11/2024 19:42:41 - INFO - trainer -     slot_precision = 0.9258883248730965\n","09/11/2024 19:42:41 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 41 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:43:00 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:43:00 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:43:00 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.67it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.69it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.74it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.69it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.09it/s]\n","09/11/2024 19:43:02 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:43:02 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:43:02 - INFO - trainer -     loss = 1.6562313002401166\n","09/11/2024 19:43:02 - INFO - trainer -     mean_intent_slot = 0.8694048056240491\n","09/11/2024 19:43:02 - INFO - trainer -     semantic_frame_acc = 0.6556122448979592\n","09/11/2024 19:43:02 - INFO - trainer -     slot_f1 = 0.9377892030848329\n","09/11/2024 19:43:02 - INFO - trainer -     slot_precision = 0.9258883248730965\n","09/11/2024 19:43:02 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 42 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:18<00:00,  2.81it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:43:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:43:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:43:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.03it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.30it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 19:43:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:43:22 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 19:43:22 - INFO - trainer -     loss = 1.6386752017174981\n","09/11/2024 19:43:22 - INFO - trainer -     mean_intent_slot = 0.8696460065507684\n","09/11/2024 19:43:22 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:43:22 - INFO - trainer -     slot_f1 = 0.9382716049382716\n","09/11/2024 19:43:22 - INFO - trainer -     slot_precision = 0.926829268292683\n","09/11/2024 19:43:22 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 43 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:43:41 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:43:41 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:43:41 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.16it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.23it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.28it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 19:43:42 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:43:42 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 19:43:42 - INFO - trainer -     loss = 1.6212470190200423\n","09/11/2024 19:43:42 - INFO - trainer -     mean_intent_slot = 0.870407113462669\n","09/11/2024 19:43:42 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:43:42 - INFO - trainer -     slot_f1 = 0.9372427983539094\n","09/11/2024 19:43:42 - INFO - trainer -     slot_precision = 0.9258130081300813\n","09/11/2024 19:43:42 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 44 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:18<00:00,  2.88it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:44:01 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:44:01 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:44:01 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.68it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.54it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.63it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.68it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.05it/s]\n","09/11/2024 19:44:03 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:44:03 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 19:44:03 - INFO - trainer -     loss = 1.6168541507462837\n","09/11/2024 19:44:03 - INFO - trainer -     mean_intent_slot = 0.8706482979192707\n","09/11/2024 19:44:03 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:44:03 - INFO - trainer -     slot_f1 = 0.9377251672671126\n","09/11/2024 19:44:03 - INFO - trainer -     slot_precision = 0.9267548321464903\n","09/11/2024 19:44:03 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 45 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:44:21 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:44:21 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:44:21 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.29it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.87it/s]\n","09/11/2024 19:44:23 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:44:23 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 19:44:23 - INFO - trainer -     loss = 1.616943550894835\n","09/11/2024 19:44:23 - INFO - trainer -     mean_intent_slot = 0.8706482979192707\n","09/11/2024 19:44:23 - INFO - trainer -     semantic_frame_acc = 0.6581632653061225\n","09/11/2024 19:44:23 - INFO - trainer -     slot_f1 = 0.9377251672671126\n","09/11/2024 19:44:23 - INFO - trainer -     slot_precision = 0.9267548321464903\n","09/11/2024 19:44:23 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 46 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Epoch: 100% 50/50 [17:03<00:00, 20.48s/it]\n","09/11/2024 19:44:23 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 19:44:23 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 19:44:23 - INFO - trainer -     Num examples = 346\n","09/11/2024 19:44:23 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.73it/s]\n","09/11/2024 19:44:25 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:44:25 - INFO - trainer -     intent_acc = 0.8526011560693642\n","09/11/2024 19:44:25 - INFO - trainer -     loss = 1.9157207508881886\n","09/11/2024 19:44:25 - INFO - trainer -     mean_intent_slot = 0.8830985449978332\n","09/11/2024 19:44:25 - INFO - trainer -     semantic_frame_acc = 0.6358381502890174\n","09/11/2024 19:44:25 - INFO - trainer -     slot_f1 = 0.9135959339263025\n","09/11/2024 19:44:25 - INFO - trainer -     slot_precision = 0.89875\n","09/11/2024 19:44:25 - INFO - trainer -     slot_recall = 0.9289405684754521\n"]}]},{"cell_type":"code","source":["# First, run the previous bash script to train JointBERT-CRF_PhoBERTencoder\n","# !bash run_jointBERT-CRF_PhoBERTencoder.sh\n","\n","# Now set up environment variables for the new training run\n","lr = \"4e-5\"\n","c = \"0.2\"\n","s = \"100\"\n","\n","# Display the variables\n","print(lr)\n","\n","# Set the MODEL_DIR path for JointIDSF\n","MODEL_DIR = f\"Model_Hackathon/JointIDSF_CLPhoBERTencoder/{lr}/{c}/{s}\"\n","print(MODEL_DIR)\n","\n","# Run the second python script using the pretrained model path\n","!python3 main.py --token_level word-level \\\n","                  --model_type clphobert \\\n","                  --model_dir $MODEL_DIR \\\n","                  --data_dir Hackathon \\\n","                  --seed $s \\\n","                  --do_train \\\n","                  --do_eval \\\n","                  --save_steps 56 \\\n","                  --logging_steps 56 \\\n","                  --num_train_epochs 50 \\\n","                  --tuning_metric mean_intent_slot \\\n","                  --use_intent_context_attention \\\n","                  --attention_embedding_size 200 \\\n","                  --use_crf \\\n","                  --gpu_id 0 \\\n","                  --embedding_type soft \\\n","                  --intent_loss_coef $c \\\n","                  --pretrained \\\n","                  --pretrained_path Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 \\\n","                  --learning_rate $lr\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"M6nnptr3n0oL","executionInfo":{"status":"ok","timestamp":1726085055991,"user_tz":-420,"elapsed":1044818,"user":{"displayName":"Trung Thanh Nguyen","userId":"17922774632869085407"}},"outputId":"509707ab-e92d-4071-977a-f4efe3cf74ee"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["4e-5\n","Model_Hackathon/JointIDSF_CLPhoBERTencoder/4e-5/0.2/100\n","2024-09-11 19:47:03.374578: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-09-11 19:47:03.395009: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-09-11 19:47:03.401085: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","2024-09-11 19:47:03.415819: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2024-09-11 19:47:04.961506: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","09/11/2024 19:47:07 - INFO - data_loader -   Loading features from cached file Hackathon/cached_train_word-level_clphobert-base-16-256-50-30_50\n","/content/ViNLU/data_loader.py:238: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n","  features = torch.load(cached_features_file)\n","09/11/2024 19:47:07 - INFO - data_loader -   Loading features from cached file Hackathon/cached_dev_word-level_clphobert-base-16-256-50-30_50\n","09/11/2024 19:47:07 - INFO - data_loader -   Loading features from cached file Hackathon/cached_test_word-level_clphobert-base-16-256-50-30_50\n","phongtintruong/clphobert-base-16-256-50-30\n","Some weights of JointPhoBERT were not initialized from the model checkpoint at Model_Hackathon/JointBERT-CRF_CLPhoBERTencoder/3e-5/0.8/100 and are newly initialized: ['slot_classifier.attention.linear_out.weight', 'slot_classifier.linear_intent_context.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","0\n","0\n","check init\n","09/11/2024 19:47:07 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:47:07 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:47:07 - INFO - trainer -     Batch size = 64\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/torchcrf/__init__.py:249: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at ../aten/src/ATen/native/TensorCompare.cpp:530.)\n","  score = torch.where(mask[i].unsqueeze(1), next_score, score)\n","Evaluating: 100% 7/7 [00:02<00:00,  3.31it/s]\n","/usr/local/lib/python3.10/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: PAD seems not to be NE tag.\n","  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n","09/11/2024 19:47:10 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:47:10 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 19:47:10 - INFO - trainer -     loss = 30.87683868408203\n","09/11/2024 19:47:10 - INFO - trainer -     mean_intent_slot = 0.4339380645369787\n","09/11/2024 19:47:10 - INFO - trainer -     semantic_frame_acc = 0.0\n","09/11/2024 19:47:10 - INFO - trainer -     slot_f1 = 0.015835312747426764\n","09/11/2024 19:47:10 - INFO - trainer -     slot_precision = 0.010604453870625663\n","09/11/2024 19:47:10 - INFO - trainer -     slot_recall = 0.03125\n","{'loss': 30.87683868408203, 'intent_acc': 0.8520408163265306, 'slot_precision': 0.010604453870625663, 'slot_recall': 0.03125, 'slot_f1': 0.015835312747426764, 'semantic_frame_acc': 0.0, 'mean_intent_slot': 0.4339380645369787}\n","/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:591: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n","  warnings.warn(\n","09/11/2024 19:47:10 - INFO - trainer -   ***** Running training *****\n","09/11/2024 19:47:10 - INFO - trainer -     Num examples = 1790\n","09/11/2024 19:47:10 - INFO - trainer -     Num Epochs = 50\n","09/11/2024 19:47:10 - INFO - trainer -     Total train batch size = 32\n","09/11/2024 19:47:10 - INFO - trainer -     Gradient Accumulation steps = 1\n","09/11/2024 19:47:10 - INFO - trainer -     Total optimization steps = 2800\n","09/11/2024 19:47:10 - INFO - trainer -     Logging steps = 56\n","09/11/2024 19:47:10 - INFO - trainer -     Save steps = 56\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 0\n","Iteration:  98% 55/56 [00:17<00:00,  3.27it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:47:27 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:47:27 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:47:27 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.45it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.52it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.55it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.56it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.10it/s]\n","09/11/2024 19:47:29 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:47:29 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:47:29 - INFO - trainer -     loss = 10.428272724151611\n","09/11/2024 19:47:29 - INFO - trainer -     mean_intent_slot = 0.8496888870012105\n","09/11/2024 19:47:29 - INFO - trainer -     semantic_frame_acc = 0.3239795918367347\n","09/11/2024 19:47:29 - INFO - trainer -     slot_f1 = 0.86264308012487\n","09/11/2024 19:47:29 - INFO - trainer -     slot_precision = 0.8617463617463618\n","09/11/2024 19:47:29 - INFO - trainer -     slot_recall = 0.8635416666666667\n","mean_intent_slot increased (inf --> 0.849689).  Saving model ...\n","Iteration: 100% 56/56 [00:23<00:00,  2.40it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 1\n","Iteration:  98% 55/56 [00:17<00:00,  3.12it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:47:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:47:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:47:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.59it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.50it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.45it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  5.02it/s]\n","09/11/2024 19:47:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:47:52 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 19:47:52 - INFO - trainer -     loss = 4.584375407014575\n","09/11/2024 19:47:52 - INFO - trainer -     mean_intent_slot = 0.8605192076830732\n","09/11/2024 19:47:52 - INFO - trainer -     semantic_frame_acc = 0.5867346938775511\n","09/11/2024 19:47:52 - INFO - trainer -     slot_f1 = 0.9149159663865546\n","09/11/2024 19:47:52 - INFO - trainer -     slot_precision = 0.9226694915254238\n","09/11/2024 19:47:52 - INFO - trainer -     slot_recall = 0.9072916666666667\n","mean_intent_slot increased (0.849689 --> 0.860519).  Saving model ...\n","Iteration: 100% 56/56 [00:21<00:00,  2.58it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 2\n","Iteration:  98% 55/56 [00:18<00:00,  3.10it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:48:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:48:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:48:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.56it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.84it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.93it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.34it/s]\n","09/11/2024 19:48:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:48:15 - INFO - trainer -     intent_acc = 0.8647959183673469\n","09/11/2024 19:48:15 - INFO - trainer -     loss = 2.6449875150408064\n","09/11/2024 19:48:15 - INFO - trainer -     mean_intent_slot = 0.8929379384152414\n","09/11/2024 19:48:15 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:48:15 - INFO - trainer -     slot_f1 = 0.921079958463136\n","09/11/2024 19:48:15 - INFO - trainer -     slot_precision = 0.9182194616977226\n","09/11/2024 19:48:15 - INFO - trainer -     slot_recall = 0.9239583333333333\n","mean_intent_slot increased (0.860519 --> 0.892938).  Saving model ...\n","Iteration: 100% 56/56 [00:30<00:00,  1.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 3\n","Iteration:  98% 55/56 [00:18<00:00,  2.78it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:48:45 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:48:45 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:48:45 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.91it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.04it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.01it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.10it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.04it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.58it/s]\n","09/11/2024 19:48:46 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:48:46 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:48:46 - INFO - trainer -     loss = 1.8861550177846635\n","09/11/2024 19:48:46 - INFO - trainer -     mean_intent_slot = 0.8834238731463808\n","09/11/2024 19:48:46 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:48:46 - INFO - trainer -     slot_f1 = 0.9301130524152107\n","09/11/2024 19:48:46 - INFO - trainer -     slot_precision = 0.9178498985801217\n","09/11/2024 19:48:46 - INFO - trainer -     slot_recall = 0.9427083333333334\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.70it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 4\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:49:05 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:49:05 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:49:05 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.09it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.30it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:49:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:49:07 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:49:07 - INFO - trainer -     loss = 1.480220424277442\n","09/11/2024 19:49:07 - INFO - trainer -     mean_intent_slot = 0.8791144221184618\n","09/11/2024 19:49:07 - INFO - trainer -     semantic_frame_acc = 0.673469387755102\n","09/11/2024 19:49:07 - INFO - trainer -     slot_f1 = 0.9419023136246787\n","09/11/2024 19:49:07 - INFO - trainer -     slot_precision = 0.9299492385786802\n","09/11/2024 19:49:07 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 5\n","Iteration:  98% 55/56 [00:18<00:00,  2.98it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:49:25 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:49:25 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:49:25 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.85it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.72it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.76it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.31it/s]\n","09/11/2024 19:49:27 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:49:27 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:49:27 - INFO - trainer -     loss = 1.3231328566159521\n","09/11/2024 19:49:27 - INFO - trainer -     mean_intent_slot = 0.8883776882004094\n","09/11/2024 19:49:27 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 19:49:27 - INFO - trainer -     slot_f1 = 0.9400206825232678\n","09/11/2024 19:49:27 - INFO - trainer -     slot_precision = 0.9332648870636551\n","09/11/2024 19:49:27 - INFO - trainer -     slot_recall = 0.946875\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 6\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:49:46 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:49:46 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:49:46 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.37it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.38it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.93it/s]\n","09/11/2024 19:49:47 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:49:47 - INFO - trainer -     intent_acc = 0.8239795918367347\n","09/11/2024 19:49:47 - INFO - trainer -     loss = 1.3804514450686318\n","09/11/2024 19:49:47 - INFO - trainer -     mean_intent_slot = 0.8789298266718271\n","09/11/2024 19:49:47 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 19:49:47 - INFO - trainer -     slot_f1 = 0.9338800615069195\n","09/11/2024 19:49:47 - INFO - trainer -     slot_precision = 0.9192734611503531\n","09/11/2024 19:49:47 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 7\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:50:06 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:50:06 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:50:06 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.92it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.84it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.87it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.29it/s]\n","09/11/2024 19:50:07 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:50:07 - INFO - trainer -     intent_acc = 0.8290816326530612\n","09/11/2024 19:50:07 - INFO - trainer -     loss = 1.4012415185570717\n","09/11/2024 19:50:07 - INFO - trainer -     mean_intent_slot = 0.8807639483633781\n","09/11/2024 19:50:07 - INFO - trainer -     semantic_frame_acc = 0.6683673469387755\n","09/11/2024 19:50:07 - INFO - trainer -     slot_f1 = 0.932446264073695\n","09/11/2024 19:50:07 - INFO - trainer -     slot_precision = 0.9164989939637826\n","09/11/2024 19:50:07 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 8\n","Iteration:  98% 55/56 [00:18<00:00,  3.02it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:50:26 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:50:26 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:50:26 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.05it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:50:28 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:50:28 - INFO - trainer -     intent_acc = 0.8673469387755102\n","09/11/2024 19:50:28 - INFO - trainer -     loss = 1.222475972824863\n","09/11/2024 19:50:28 - INFO - trainer -     mean_intent_slot = 0.9043222850417201\n","09/11/2024 19:50:28 - INFO - trainer -     semantic_frame_acc = 0.7219387755102041\n","09/11/2024 19:50:28 - INFO - trainer -     slot_f1 = 0.9412976313079299\n","09/11/2024 19:50:28 - INFO - trainer -     slot_precision = 0.9307535641547862\n","09/11/2024 19:50:28 - INFO - trainer -     slot_recall = 0.9520833333333333\n","mean_intent_slot increased (0.892938 --> 0.904322).  Saving model ...\n","Iteration: 100% 56/56 [00:22<00:00,  2.45it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 9\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:50:49 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:50:49 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:50:49 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.84it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.76it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.65it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.16it/s]\n","09/11/2024 19:50:51 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:50:51 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:50:51 - INFO - trainer -     loss = 1.262113789362567\n","09/11/2024 19:50:51 - INFO - trainer -     mean_intent_slot = 0.8849995249004932\n","09/11/2024 19:50:51 - INFO - trainer -     semantic_frame_acc = 0.701530612244898\n","09/11/2024 19:50:51 - INFO - trainer -     slot_f1 = 0.9332643559234352\n","09/11/2024 19:50:51 - INFO - trainer -     slot_precision = 0.9270298047276464\n","09/11/2024 19:50:51 - INFO - trainer -     slot_recall = 0.9395833333333333\n","EarlyStopping counter: 1 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 10\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:51:10 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:51:10 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:51:10 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.26it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.76it/s]\n","09/11/2024 19:51:11 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:51:11 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:51:11 - INFO - trainer -     loss = 1.4609532851193632\n","09/11/2024 19:51:11 - INFO - trainer -     mean_intent_slot = 0.8790117273903426\n","09/11/2024 19:51:11 - INFO - trainer -     semantic_frame_acc = 0.6709183673469388\n","09/11/2024 19:51:11 - INFO - trainer -     slot_f1 = 0.9314928425357873\n","09/11/2024 19:51:11 - INFO - trainer -     slot_precision = 0.9146586345381527\n","09/11/2024 19:51:11 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 2 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 11\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:51:30 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:51:30 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:51:30 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.92it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.35it/s]\n","09/11/2024 19:51:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:51:32 - INFO - trainer -     intent_acc = 0.8112244897959183\n","09/11/2024 19:51:32 - INFO - trainer -     loss = 1.5310136399098806\n","09/11/2024 19:51:32 - INFO - trainer -     mean_intent_slot = 0.87013496056922\n","09/11/2024 19:51:32 - INFO - trainer -     semantic_frame_acc = 0.6377551020408163\n","09/11/2024 19:51:32 - INFO - trainer -     slot_f1 = 0.9290454313425217\n","09/11/2024 19:51:32 - INFO - trainer -     slot_precision = 0.9109109109109109\n","09/11/2024 19:51:32 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 3 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 12\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:51:50 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:51:50 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:51:50 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 19:51:52 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:51:52 - INFO - trainer -     intent_acc = 0.8163265306122449\n","09/11/2024 19:51:52 - INFO - trainer -     loss = 1.2314658030601484\n","09/11/2024 19:51:52 - INFO - trainer -     mean_intent_slot = 0.8789944475467006\n","09/11/2024 19:51:52 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:51:52 - INFO - trainer -     slot_f1 = 0.9416623644811564\n","09/11/2024 19:51:52 - INFO - trainer -     slot_precision = 0.9334698055271239\n","09/11/2024 19:51:52 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 4 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 13\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:52:11 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:52:11 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:52:11 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.10it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.19it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.04it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.60it/s]\n","09/11/2024 19:52:12 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:52:12 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 19:52:12 - INFO - trainer -     loss = 1.2915616425286447\n","09/11/2024 19:52:12 - INFO - trainer -     mean_intent_slot = 0.8809095580678314\n","09/11/2024 19:52:12 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:52:12 - INFO - trainer -     slot_f1 = 0.9403905447070915\n","09/11/2024 19:52:12 - INFO - trainer -     slot_precision = 0.9279918864097363\n","09/11/2024 19:52:12 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 5 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 14\n","Iteration:  98% 55/56 [00:18<00:00,  3.01it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:52:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:52:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:52:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.19it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 19:52:32 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:52:32 - INFO - trainer -     intent_acc = 0.7933673469387755\n","09/11/2024 19:52:32 - INFO - trainer -     loss = 1.4129145254514046\n","09/11/2024 19:52:32 - INFO - trainer -     mean_intent_slot = 0.8648561580689771\n","09/11/2024 19:52:32 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:52:32 - INFO - trainer -     slot_f1 = 0.9363449691991786\n","09/11/2024 19:52:32 - INFO - trainer -     slot_precision = 0.9230769230769231\n","09/11/2024 19:52:32 - INFO - trainer -     slot_recall = 0.95\n","EarlyStopping counter: 6 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 15\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:52:51 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:52:51 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:52:51 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.14it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.24it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.68it/s]\n","09/11/2024 19:52:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:52:53 - INFO - trainer -     intent_acc = 0.8086734693877551\n","09/11/2024 19:52:53 - INFO - trainer -     loss = 1.5197248396330647\n","09/11/2024 19:52:53 - INFO - trainer -     mean_intent_slot = 0.8716216393821825\n","09/11/2024 19:52:53 - INFO - trainer -     semantic_frame_acc = 0.6607142857142857\n","09/11/2024 19:52:53 - INFO - trainer -     slot_f1 = 0.93456980937661\n","09/11/2024 19:52:53 - INFO - trainer -     slot_precision = 0.9245667686034659\n","09/11/2024 19:52:53 - INFO - trainer -     slot_recall = 0.9447916666666667\n","EarlyStopping counter: 7 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 16\n","Iteration:  98% 55/56 [00:18<00:00,  2.91it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:53:11 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:53:11 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:53:11 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.27it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 19:53:13 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:53:13 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 19:53:13 - INFO - trainer -     loss = 1.5557628385722637\n","09/11/2024 19:53:13 - INFO - trainer -     mean_intent_slot = 0.8686669739764489\n","09/11/2024 19:53:13 - INFO - trainer -     semantic_frame_acc = 0.6403061224489796\n","09/11/2024 19:53:13 - INFO - trainer -     slot_f1 = 0.9312114989733059\n","09/11/2024 19:53:13 - INFO - trainer -     slot_precision = 0.9180161943319838\n","09/11/2024 19:53:13 - INFO - trainer -     slot_recall = 0.9447916666666667\n","EarlyStopping counter: 8 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 17\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:53:31 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:53:31 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:53:31 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.89it/s]\n","09/11/2024 19:53:33 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:53:33 - INFO - trainer -     intent_acc = 0.8214285714285714\n","09/11/2024 19:53:33 - INFO - trainer -     loss = 1.8120280912678157\n","09/11/2024 19:53:33 - INFO - trainer -     mean_intent_slot = 0.8684105140527159\n","09/11/2024 19:53:33 - INFO - trainer -     semantic_frame_acc = 0.6326530612244898\n","09/11/2024 19:53:33 - INFO - trainer -     slot_f1 = 0.9153924566768603\n","09/11/2024 19:53:33 - INFO - trainer -     slot_precision = 0.8962075848303394\n","09/11/2024 19:53:33 - INFO - trainer -     slot_recall = 0.9354166666666667\n","EarlyStopping counter: 9 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 18\n","Iteration:  98% 55/56 [00:18<00:00,  2.86it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:53:52 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:53:52 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:53:52 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.66it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.63it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.45it/s]\n","09/11/2024 19:53:53 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:53:53 - INFO - trainer -     intent_acc = 0.8367346938775511\n","09/11/2024 19:53:53 - INFO - trainer -     loss = 1.521265105211309\n","09/11/2024 19:53:53 - INFO - trainer -     mean_intent_slot = 0.882597918220299\n","09/11/2024 19:53:53 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 19:53:53 - INFO - trainer -     slot_f1 = 0.9284611425630468\n","09/11/2024 19:53:53 - INFO - trainer -     slot_precision = 0.9175991861648016\n","09/11/2024 19:53:53 - INFO - trainer -     slot_recall = 0.9395833333333333\n","EarlyStopping counter: 10 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 19\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:54:12 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:54:12 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:54:12 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 19:54:14 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:54:14 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:54:14 - INFO - trainer -     loss = 1.4651400073032295\n","09/11/2024 19:54:14 - INFO - trainer -     mean_intent_slot = 0.8827368299808378\n","09/11/2024 19:54:14 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:54:14 - INFO - trainer -     slot_f1 = 0.9389430477167777\n","09/11/2024 19:54:14 - INFO - trainer -     slot_precision = 0.9251769464105156\n","09/11/2024 19:54:14 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 11 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 20\n","Iteration:  98% 55/56 [00:18<00:00,  2.89it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:54:32 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:54:32 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:54:32 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.63it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.60it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.61it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.67it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.15it/s]\n","09/11/2024 19:54:34 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:54:34 - INFO - trainer -     intent_acc = 0.8290816326530612\n","09/11/2024 19:54:34 - INFO - trainer -     loss = 1.4756483547389507\n","09/11/2024 19:54:34 - INFO - trainer -     mean_intent_slot = 0.8832908163265306\n","09/11/2024 19:54:34 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:54:34 - INFO - trainer -     slot_f1 = 0.9375\n","09/11/2024 19:54:34 - INFO - trainer -     slot_precision = 0.9223790322580645\n","09/11/2024 19:54:34 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 12 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.73it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 21\n","Iteration:  98% 55/56 [00:18<00:00,  2.95it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:54:53 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:54:53 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:54:53 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.89it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.75it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.71it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.21it/s]\n","09/11/2024 19:54:54 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:54:54 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 19:54:54 - INFO - trainer -     loss = 1.4594583314444338\n","09/11/2024 19:54:54 - INFO - trainer -     mean_intent_slot = 0.8893960710886097\n","09/11/2024 19:54:54 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:54:54 - INFO - trainer -     slot_f1 = 0.9369554074833419\n","09/11/2024 19:54:54 - INFO - trainer -     slot_precision = 0.922300706357215\n","09/11/2024 19:54:54 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 13 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 22\n","Iteration:  98% 55/56 [00:18<00:00,  2.95it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:55:13 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:55:13 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:55:13 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.86it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.96it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.85it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.31it/s]\n","09/11/2024 19:55:15 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:55:15 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 19:55:15 - INFO - trainer -     loss = 1.6093770446521896\n","09/11/2024 19:55:15 - INFO - trainer -     mean_intent_slot = 0.8881572076118063\n","09/11/2024 19:55:15 - INFO - trainer -     semantic_frame_acc = 0.6785714285714286\n","09/11/2024 19:55:15 - INFO - trainer -     slot_f1 = 0.9293756397134084\n","09/11/2024 19:55:15 - INFO - trainer -     slot_precision = 0.9134808853118712\n","09/11/2024 19:55:15 - INFO - trainer -     slot_recall = 0.9458333333333333\n","EarlyStopping counter: 14 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 23\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:55:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:55:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:55:34 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.22it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.26it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.80it/s]\n","09/11/2024 19:55:35 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:55:35 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:55:35 - INFO - trainer -     loss = 1.512172952693488\n","09/11/2024 19:55:35 - INFO - trainer -     mean_intent_slot = 0.8878805620608898\n","09/11/2024 19:55:35 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:55:35 - INFO - trainer -     slot_f1 = 0.9364754098360655\n","09/11/2024 19:55:35 - INFO - trainer -     slot_precision = 0.9213709677419355\n","09/11/2024 19:55:35 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 15 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 24\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:55:54 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:55:54 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:55:54 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.43it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.86it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.32it/s]\n","09/11/2024 19:55:55 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:55:55 - INFO - trainer -     intent_acc = 0.8494897959183674\n","09/11/2024 19:55:55 - INFO - trainer -     loss = 1.375677352771163\n","09/11/2024 19:55:55 - INFO - trainer -     mean_intent_slot = 0.8937851456372022\n","09/11/2024 19:55:55 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 19:55:55 - INFO - trainer -     slot_f1 = 0.9380804953560371\n","09/11/2024 19:55:55 - INFO - trainer -     slot_precision = 0.9294478527607362\n","09/11/2024 19:55:55 - INFO - trainer -     slot_recall = 0.946875\n","EarlyStopping counter: 16 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 25\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:56:14 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:56:14 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:56:14 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.34it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.36it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.91it/s]\n","09/11/2024 19:56:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:56:16 - INFO - trainer -     intent_acc = 0.8520408163265306\n","09/11/2024 19:56:16 - INFO - trainer -     loss = 1.4592429636312383\n","09/11/2024 19:56:16 - INFO - trainer -     mean_intent_slot = 0.8921046836000588\n","09/11/2024 19:56:16 - INFO - trainer -     semantic_frame_acc = 0.6964285714285714\n","09/11/2024 19:56:16 - INFO - trainer -     slot_f1 = 0.9321685508735869\n","09/11/2024 19:56:16 - INFO - trainer -     slot_precision = 0.9198782961460447\n","09/11/2024 19:56:16 - INFO - trainer -     slot_recall = 0.9447916666666667\n","EarlyStopping counter: 17 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 26\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:56:34 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:56:34 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:56:34 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.27it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.37it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.90it/s]\n","09/11/2024 19:56:36 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:56:36 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 19:56:36 - INFO - trainer -     loss = 1.3671506816255194\n","09/11/2024 19:56:36 - INFO - trainer -     mean_intent_slot = 0.8932680454732229\n","09/11/2024 19:56:36 - INFO - trainer -     semantic_frame_acc = 0.7117346938775511\n","09/11/2024 19:56:36 - INFO - trainer -     slot_f1 = 0.9395973154362416\n","09/11/2024 19:56:36 - INFO - trainer -     slot_precision = 0.9314227226202662\n","09/11/2024 19:56:36 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 18 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 27\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:56:55 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:56:55 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:56:55 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.01it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:56:56 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:56:56 - INFO - trainer -     intent_acc = 0.8469387755102041\n","09/11/2024 19:56:56 - INFO - trainer -     loss = 1.3747708887926169\n","09/11/2024 19:56:56 - INFO - trainer -     mean_intent_slot = 0.8962340331816181\n","09/11/2024 19:56:56 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 19:56:56 - INFO - trainer -     slot_f1 = 0.945529290853032\n","09/11/2024 19:56:56 - INFO - trainer -     slot_precision = 0.9330628803245437\n","09/11/2024 19:56:56 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 19 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 28\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:57:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:57:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:57:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.28it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.30it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 19:57:16 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:57:16 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 19:57:16 - INFO - trainer -     loss = 1.3713895695816194\n","09/11/2024 19:57:16 - INFO - trainer -     mean_intent_slot = 0.8880955873108998\n","09/11/2024 19:57:16 - INFO - trainer -     semantic_frame_acc = 0.6938775510204082\n","09/11/2024 19:57:16 - INFO - trainer -     slot_f1 = 0.944558521560575\n","09/11/2024 19:57:16 - INFO - trainer -     slot_precision = 0.9311740890688259\n","09/11/2024 19:57:16 - INFO - trainer -     slot_recall = 0.9583333333333334\n","EarlyStopping counter: 20 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 29\n","Iteration:  98% 55/56 [00:18<00:00,  2.82it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:57:35 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:57:35 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:57:35 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.68it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.13it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.21it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.65it/s]\n","09/11/2024 19:57:36 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:57:36 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:57:36 - INFO - trainer -     loss = 1.4314347747048097\n","09/11/2024 19:57:36 - INFO - trainer -     mean_intent_slot = 0.8897767397381198\n","09/11/2024 19:57:36 - INFO - trainer -     semantic_frame_acc = 0.6887755102040817\n","09/11/2024 19:57:36 - INFO - trainer -     slot_f1 = 0.9402677651905254\n","09/11/2024 19:57:36 - INFO - trainer -     slot_precision = 0.929735234215886\n","09/11/2024 19:57:36 - INFO - trainer -     slot_recall = 0.9510416666666667\n","EarlyStopping counter: 21 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 30\n","Iteration:  98% 55/56 [00:18<00:00,  3.03it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:57:55 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:57:55 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:57:55 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 19:57:57 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:57:57 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:57:57 - INFO - trainer -     loss = 1.4709765522607736\n","09/11/2024 19:57:57 - INFO - trainer -     mean_intent_slot = 0.8876840942562592\n","09/11/2024 19:57:57 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:57:57 - INFO - trainer -     slot_f1 = 0.9360824742268041\n","09/11/2024 19:57:57 - INFO - trainer -     slot_precision = 0.926530612244898\n","09/11/2024 19:57:57 - INFO - trainer -     slot_recall = 0.9458333333333333\n","EarlyStopping counter: 22 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 31\n","Iteration:  98% 55/56 [00:18<00:00,  2.96it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:58:15 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:58:15 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:58:15 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.70it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.70it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.68it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.15it/s]\n","09/11/2024 19:58:17 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:58:17 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 19:58:17 - INFO - trainer -     loss = 1.504159220294761\n","09/11/2024 19:58:17 - INFO - trainer -     mean_intent_slot = 0.8836826504380673\n","09/11/2024 19:58:17 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:58:17 - INFO - trainer -     slot_f1 = 0.93573264781491\n","09/11/2024 19:58:17 - INFO - trainer -     slot_precision = 0.9238578680203046\n","09/11/2024 19:58:17 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 23 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 32\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:58:36 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:58:36 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:58:36 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.07it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.84it/s]\n","09/11/2024 19:58:37 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:58:37 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 19:58:37 - INFO - trainer -     loss = 1.3255364238949758\n","09/11/2024 19:58:37 - INFO - trainer -     mean_intent_slot = 0.888929046282422\n","09/11/2024 19:58:37 - INFO - trainer -     semantic_frame_acc = 0.7091836734693877\n","09/11/2024 19:58:37 - INFO - trainer -     slot_f1 = 0.9462254395036195\n","09/11/2024 19:58:37 - INFO - trainer -     slot_precision = 0.9394250513347022\n","09/11/2024 19:58:37 - INFO - trainer -     slot_recall = 0.953125\n","EarlyStopping counter: 24 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 33\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:58:56 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:58:56 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:58:56 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.08it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.22it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.78it/s]\n","09/11/2024 19:58:58 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:58:58 - INFO - trainer -     intent_acc = 0.826530612244898\n","09/11/2024 19:58:58 - INFO - trainer -     loss = 1.3995996923851115\n","09/11/2024 19:58:58 - INFO - trainer -     mean_intent_slot = 0.8839141217764139\n","09/11/2024 19:58:58 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:58:58 - INFO - trainer -     slot_f1 = 0.9412976313079299\n","09/11/2024 19:58:58 - INFO - trainer -     slot_precision = 0.9307535641547862\n","09/11/2024 19:58:58 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 25 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 34\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:59:16 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:59:16 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:59:16 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.02it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.23it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.28it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.32it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.33it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.85it/s]\n","09/11/2024 19:59:18 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:59:18 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:59:18 - INFO - trainer -     loss = 1.5638696679047175\n","09/11/2024 19:59:18 - INFO - trainer -     mean_intent_slot = 0.8832803613248578\n","09/11/2024 19:59:18 - INFO - trainer -     semantic_frame_acc = 0.6836734693877551\n","09/11/2024 19:59:18 - INFO - trainer -     slot_f1 = 0.9323770491803278\n","09/11/2024 19:59:18 - INFO - trainer -     slot_precision = 0.9173387096774194\n","09/11/2024 19:59:18 - INFO - trainer -     slot_recall = 0.9479166666666666\n","EarlyStopping counter: 26 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 35\n","Iteration:  98% 55/56 [00:18<00:00,  3.06it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:59:36 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:59:36 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:59:36 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.12it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.29it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.78it/s]\n","09/11/2024 19:59:38 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:59:38 - INFO - trainer -     intent_acc = 0.8341836734693877\n","09/11/2024 19:59:38 - INFO - trainer -     loss = 1.60584897388305\n","09/11/2024 19:59:38 - INFO - trainer -     mean_intent_slot = 0.8828382580025875\n","09/11/2024 19:59:38 - INFO - trainer -     semantic_frame_acc = 0.6862244897959183\n","09/11/2024 19:59:38 - INFO - trainer -     slot_f1 = 0.9314928425357873\n","09/11/2024 19:59:38 - INFO - trainer -     slot_precision = 0.9146586345381527\n","09/11/2024 19:59:38 - INFO - trainer -     slot_recall = 0.9489583333333333\n","EarlyStopping counter: 27 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 36\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 19:59:57 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 19:59:57 - INFO - trainer -     Num examples = 392\n","09/11/2024 19:59:57 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.77it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.79it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.75it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.96it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.11it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.59it/s]\n","09/11/2024 19:59:58 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 19:59:58 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 19:59:58 - INFO - trainer -     loss = 1.514983210380056\n","09/11/2024 19:59:58 - INFO - trainer -     mean_intent_slot = 0.8898687298327956\n","09/11/2024 19:59:58 - INFO - trainer -     semantic_frame_acc = 0.6913265306122449\n","09/11/2024 19:59:58 - INFO - trainer -     slot_f1 = 0.9404517453798769\n","09/11/2024 19:59:58 - INFO - trainer -     slot_precision = 0.9271255060728745\n","09/11/2024 19:59:58 - INFO - trainer -     slot_recall = 0.9541666666666667\n","EarlyStopping counter: 28 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 37\n","Iteration:  98% 55/56 [00:18<00:00,  3.08it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:00:17 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:00:17 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:00:17 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.21it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.35it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.36it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.35it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.88it/s]\n","09/11/2024 20:00:18 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:00:18 - INFO - trainer -     intent_acc = 0.8418367346938775\n","09/11/2024 20:00:18 - INFO - trainer -     loss = 1.435490018222481\n","09/11/2024 20:00:18 - INFO - trainer -     mean_intent_slot = 0.8920523879654955\n","09/11/2024 20:00:18 - INFO - trainer -     semantic_frame_acc = 0.7040816326530612\n","09/11/2024 20:00:18 - INFO - trainer -     slot_f1 = 0.9422680412371134\n","09/11/2024 20:00:18 - INFO - trainer -     slot_precision = 0.9326530612244898\n","09/11/2024 20:00:18 - INFO - trainer -     slot_recall = 0.9520833333333333\n","EarlyStopping counter: 29 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 38\n","Iteration:  98% 55/56 [00:18<00:00,  2.92it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:00:37 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:00:37 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:00:37 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.05it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.88it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.82it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.79it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.27it/s]\n","09/11/2024 20:00:39 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:00:39 - INFO - trainer -     intent_acc = 0.8316326530612245\n","09/11/2024 20:00:39 - INFO - trainer -     loss = 2.0845331963417784\n","09/11/2024 20:00:39 - INFO - trainer -     mean_intent_slot = 0.8575248692441801\n","09/11/2024 20:00:39 - INFO - trainer -     semantic_frame_acc = 0.6096938775510204\n","09/11/2024 20:00:39 - INFO - trainer -     slot_f1 = 0.8834170854271357\n","09/11/2024 20:00:39 - INFO - trainer -     slot_precision = 0.8533980582524272\n","09/11/2024 20:00:39 - INFO - trainer -     slot_recall = 0.915625\n","EarlyStopping counter: 30 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.74it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 39\n","Iteration:  98% 55/56 [00:18<00:00,  3.05it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:00:57 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:00:57 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:00:57 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.00it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.25it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.82it/s]\n","09/11/2024 20:00:59 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:00:59 - INFO - trainer -     intent_acc = 0.8392857142857143\n","09/11/2024 20:00:59 - INFO - trainer -     loss = 1.7471215134220464\n","09/11/2024 20:00:59 - INFO - trainer -     mean_intent_slot = 0.8612339951086174\n","09/11/2024 20:00:59 - INFO - trainer -     semantic_frame_acc = 0.6224489795918368\n","09/11/2024 20:00:59 - INFO - trainer -     slot_f1 = 0.8831822759315207\n","09/11/2024 20:00:59 - INFO - trainer -     slot_precision = 0.854775828460039\n","09/11/2024 20:00:59 - INFO - trainer -     slot_recall = 0.9135416666666667\n","EarlyStopping counter: 31 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 40\n","Iteration:  98% 55/56 [00:18<00:00,  2.99it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:01:17 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:01:17 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:01:17 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.72it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.88it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.95it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.91it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.85it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.33it/s]\n","09/11/2024 20:01:19 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:01:19 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 20:01:19 - INFO - trainer -     loss = 3.390545396932534\n","09/11/2024 20:01:19 - INFO - trainer -     mean_intent_slot = 0.8051891176891177\n","09/11/2024 20:01:19 - INFO - trainer -     semantic_frame_acc = 0.3877551020408163\n","09/11/2024 20:01:19 - INFO - trainer -     slot_f1 = 0.8068068068068068\n","09/11/2024 20:01:19 - INFO - trainer -     slot_precision = 0.7764932562620424\n","09/11/2024 20:01:19 - INFO - trainer -     slot_recall = 0.8395833333333333\n","EarlyStopping counter: 32 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.76it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 41\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:01:38 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:01:38 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:01:38 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.99it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.06it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.18it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.29it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.79it/s]\n","09/11/2024 20:01:39 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:01:39 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 20:01:39 - INFO - trainer -     loss = 4.749012063656535\n","09/11/2024 20:01:39 - INFO - trainer -     mean_intent_slot = 0.6600904960524355\n","09/11/2024 20:01:39 - INFO - trainer -     semantic_frame_acc = 0.1377551020408163\n","09/11/2024 20:01:39 - INFO - trainer -     slot_f1 = 0.5191605839416058\n","09/11/2024 20:01:39 - INFO - trainer -     slot_precision = 0.46185064935064934\n","09/11/2024 20:01:39 - INFO - trainer -     slot_recall = 0.5927083333333333\n","EarlyStopping counter: 33 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.79it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 42\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:01:57 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:01:57 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:01:57 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.74it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.87it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.97it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.95it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.94it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.43it/s]\n","09/11/2024 20:01:59 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:01:59 - INFO - trainer -     intent_acc = 0.8188775510204082\n","09/11/2024 20:01:59 - INFO - trainer -     loss = 4.366976950849805\n","09/11/2024 20:01:59 - INFO - trainer -     mean_intent_slot = 0.7073792789426984\n","09/11/2024 20:01:59 - INFO - trainer -     semantic_frame_acc = 0.2066326530612245\n","09/11/2024 20:01:59 - INFO - trainer -     slot_f1 = 0.5958810068649886\n","09/11/2024 20:01:59 - INFO - trainer -     slot_precision = 0.5314285714285715\n","09/11/2024 20:01:59 - INFO - trainer -     slot_recall = 0.678125\n","EarlyStopping counter: 34 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.78it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 43\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:02:18 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:02:18 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:02:18 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 20:02:19 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:02:19 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 20:02:19 - INFO - trainer -     loss = 3.0366438712392534\n","09/11/2024 20:02:19 - INFO - trainer -     mean_intent_slot = 0.7600881261595547\n","09/11/2024 20:02:19 - INFO - trainer -     semantic_frame_acc = 0.3010204081632653\n","09/11/2024 20:02:19 - INFO - trainer -     slot_f1 = 0.7217068645640075\n","09/11/2024 20:02:19 - INFO - trainer -     slot_precision = 0.6505016722408027\n","09/11/2024 20:02:19 - INFO - trainer -     slot_recall = 0.8104166666666667\n","EarlyStopping counter: 35 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 44\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:02:38 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:02:38 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:02:38 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.15it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.98it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.80it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  3.83it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.41it/s]\n","09/11/2024 20:02:40 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:02:40 - INFO - trainer -     intent_acc = 0.7882653061224489\n","09/11/2024 20:02:40 - INFO - trainer -     loss = 3.0470704984452044\n","09/11/2024 20:02:40 - INFO - trainer -     mean_intent_slot = 0.7640532509126957\n","09/11/2024 20:02:40 - INFO - trainer -     semantic_frame_acc = 0.37244897959183676\n","09/11/2024 20:02:40 - INFO - trainer -     slot_f1 = 0.7398411957029425\n","09/11/2024 20:02:40 - INFO - trainer -     slot_precision = 0.6706181202370872\n","09/11/2024 20:02:40 - INFO - trainer -     slot_recall = 0.825\n","EarlyStopping counter: 36 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.72it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 45\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:02:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:02:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:02:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.14it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.26it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.24it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.25it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.81it/s]\n","09/11/2024 20:03:00 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:03:00 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 20:03:00 - INFO - trainer -     loss = 3.3108602352440357\n","09/11/2024 20:03:00 - INFO - trainer -     mean_intent_slot = 0.7409203430802844\n","09/11/2024 20:03:00 - INFO - trainer -     semantic_frame_acc = 0.32908163265306123\n","09/11/2024 20:03:00 - INFO - trainer -     slot_f1 = 0.683371298405467\n","09/11/2024 20:03:00 - INFO - trainer -     slot_precision = 0.6072874493927125\n","09/11/2024 20:03:00 - INFO - trainer -     slot_recall = 0.78125\n","EarlyStopping counter: 37 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 46\n","Iteration:  98% 55/56 [00:18<00:00,  3.04it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:03:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:03:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:03:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.17it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.30it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.33it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.38it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.37it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.93it/s]\n","09/11/2024 20:03:20 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:03:20 - INFO - trainer -     intent_acc = 0.798469387755102\n","09/11/2024 20:03:20 - INFO - trainer -     loss = 2.744152276377593\n","09/11/2024 20:03:20 - INFO - trainer -     mean_intent_slot = 0.7300280600810471\n","09/11/2024 20:03:20 - INFO - trainer -     semantic_frame_acc = 0.34183673469387754\n","09/11/2024 20:03:20 - INFO - trainer -     slot_f1 = 0.6615867324069923\n","09/11/2024 20:03:20 - INFO - trainer -     slot_precision = 0.5806451612903226\n","09/11/2024 20:03:20 - INFO - trainer -     slot_recall = 0.76875\n","EarlyStopping counter: 38 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.80it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 47\n","Iteration:  98% 55/56 [00:18<00:00,  2.94it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:03:39 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:03:39 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:03:39 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.13it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.25it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.32it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.83it/s]\n","09/11/2024 20:03:40 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:03:40 - INFO - trainer -     intent_acc = 0.8035714285714286\n","09/11/2024 20:03:40 - INFO - trainer -     loss = 3.0555129338588034\n","09/11/2024 20:03:40 - INFO - trainer -     mean_intent_slot = 0.7610587804553322\n","09/11/2024 20:03:40 - INFO - trainer -     semantic_frame_acc = 0.39285714285714285\n","09/11/2024 20:03:40 - INFO - trainer -     slot_f1 = 0.7185461323392358\n","09/11/2024 20:03:40 - INFO - trainer -     slot_precision = 0.6500843170320405\n","09/11/2024 20:03:40 - INFO - trainer -     slot_recall = 0.803125\n","EarlyStopping counter: 39 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.77it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 48\n","Iteration:  98% 55/56 [00:18<00:00,  3.07it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:03:59 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:03:59 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:03:59 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  4.32it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  4.31it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:00,  4.27it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:00<00:00,  4.31it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.34it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.86it/s]\n","09/11/2024 20:04:00 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:04:00 - INFO - trainer -     intent_acc = 0.8010204081632653\n","09/11/2024 20:04:00 - INFO - trainer -     loss = 2.9658173583447933\n","09/11/2024 20:04:00 - INFO - trainer -     mean_intent_slot = 0.7423632392254025\n","09/11/2024 20:04:00 - INFO - trainer -     semantic_frame_acc = 0.3647959183673469\n","09/11/2024 20:04:00 - INFO - trainer -     slot_f1 = 0.6837060702875398\n","09/11/2024 20:04:00 - INFO - trainer -     slot_precision = 0.6084484159220146\n","09/11/2024 20:04:00 - INFO - trainer -     slot_recall = 0.7802083333333333\n","EarlyStopping counter: 40 out of 50\n","Iteration: 100% 56/56 [00:19<00:00,  2.81it/s]\n","Iteration:   0% 0/56 [00:00<?, ?it/s]\n","Epoch 49\n","Iteration:  98% 55/56 [00:18<00:00,  2.81it/s]\n","Tuning metrics: mean_intent_slot\n","09/11/2024 20:04:19 - INFO - trainer -   ***** Running evaluation on dev dataset *****\n","09/11/2024 20:04:19 - INFO - trainer -     Num examples = 392\n","09/11/2024 20:04:19 - INFO - trainer -     Batch size = 64\n","\n","Evaluating:   0% 0/7 [00:00<?, ?it/s]\u001b[A\n","Evaluating:  14% 1/7 [00:00<00:01,  3.73it/s]\u001b[A\n","Evaluating:  29% 2/7 [00:00<00:01,  3.58it/s]\u001b[A\n","Evaluating:  43% 3/7 [00:00<00:01,  3.65it/s]\u001b[A\n","Evaluating:  57% 4/7 [00:01<00:00,  3.82it/s]\u001b[A\n","Evaluating:  71% 5/7 [00:01<00:00,  4.01it/s]\u001b[A\n","Evaluating: 100% 7/7 [00:01<00:00,  4.44it/s]\n","09/11/2024 20:04:21 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:04:21 - INFO - trainer -     intent_acc = 0.8061224489795918\n","09/11/2024 20:04:21 - INFO - trainer -     loss = 3.106848773679563\n","09/11/2024 20:04:21 - INFO - trainer -     mean_intent_slot = 0.7470832125795805\n","09/11/2024 20:04:21 - INFO - trainer -     semantic_frame_acc = 0.3596938775510204\n","09/11/2024 20:04:21 - INFO - trainer -     slot_f1 = 0.6880439761795694\n","09/11/2024 20:04:21 - INFO - trainer -     slot_precision = 0.6140637775960752\n","09/11/2024 20:04:21 - INFO - trainer -     slot_recall = 0.7822916666666667\n","EarlyStopping counter: 41 out of 50\n","Iteration: 100% 56/56 [00:20<00:00,  2.75it/s]\n","Epoch: 100% 50/50 [17:10<00:00, 20.62s/it]\n","09/11/2024 20:04:21 - INFO - trainer -   ***** Model Loaded *****\n","09/11/2024 20:04:21 - INFO - trainer -   ***** Running evaluation on test dataset *****\n","09/11/2024 20:04:21 - INFO - trainer -     Num examples = 346\n","09/11/2024 20:04:21 - INFO - trainer -     Batch size = 64\n","Evaluating: 100% 6/6 [00:01<00:00,  4.84it/s]\n","09/11/2024 20:04:22 - INFO - trainer -   ***** Eval results *****\n","09/11/2024 20:04:22 - INFO - trainer -     intent_acc = 0.8294797687861272\n","09/11/2024 20:04:22 - INFO - trainer -     loss = 1.661682814359665\n","09/11/2024 20:04:22 - INFO - trainer -     mean_intent_slot = 0.8711370836292189\n","09/11/2024 20:04:22 - INFO - trainer -     semantic_frame_acc = 0.638728323699422\n","09/11/2024 20:04:22 - INFO - trainer -     slot_f1 = 0.9127943984723106\n","09/11/2024 20:04:22 - INFO - trainer -     slot_precision = 0.8996235884567126\n","09/11/2024 20:04:22 - INFO - trainer -     slot_recall = 0.9263565891472868\n"]}]},{"cell_type":"code","source":["!git checkout -- ."],"metadata":{"id":"HLGvLX5e6bn8","executionInfo":{"status":"ok","timestamp":1726221753034,"user_tz":-420,"elapsed":461,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}}},"execution_count":11,"outputs":[]},{"cell_type":"code","source":["!git status"],"metadata":{"id":"Q-vdX-P81Z5d","executionInfo":{"status":"ok","timestamp":1726221761441,"user_tz":-420,"elapsed":469,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"d99633c4-0b98-402c-a32c-64f2b11b471b","colab":{"base_uri":"https://localhost:8080/"}},"execution_count":12,"outputs":[{"output_type":"stream","name":"stdout","text":["On branch main\n","Your branch is up to date with 'origin/main'.\n","\n","nothing to commit, working tree clean\n"]}]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gmEVP8gB_KQE","executionInfo":{"status":"ok","timestamp":1726221588128,"user_tz":-420,"elapsed":27406,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"c66d775b-c237-43d2-b01b-cd7fe7a165be"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["!cp /content/drive/MyDrive/ViNLU/run_baseline_hackathon.ipynb /content/ViNLU"],"metadata":{"id":"pR2UopH8BCwh","executionInfo":{"status":"ok","timestamp":1726221603409,"user_tz":-420,"elapsed":1521,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}}},"execution_count":9,"outputs":[]},{"cell_type":"code","source":["!git status"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UIblGLp6Be2u","executionInfo":{"status":"ok","timestamp":1725873909050,"user_tz":-420,"elapsed":404,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"4f5dd863-ef44-4326-dc36-b4663d63bc41"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["On branch main\n","Your branch is up to date with 'origin/main'.\n","\n","Untracked files:\n","  (use \"git add <file>...\" to include in what will be committed)\n","\t\u001b[31mHackathon/cached_dev_word-level_phobert-base_50\u001b[m\n","\t\u001b[31mHackathon/cached_test_word-level_phobert-base_50\u001b[m\n","\t\u001b[31mHackathon/cached_train_word-level_phobert-base_50\u001b[m\n","\t\u001b[31mrun_baseline_hackathon.ipynb\u001b[m\n","\n","nothing added to commit but untracked files present (use \"git add\" to track)\n"]}]},{"cell_type":"code","source":["!git add run_baseline_hackathon.ipynb"],"metadata":{"id":"zrJd44O1BhIP"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!cp -r /content/ViNLU/Model_Hackathon /content/drive/MyDrive/ViNLU/091224"],"metadata":{"id":"aADffH3EDoPh"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!git commit -m \"feat: run baseline on hackathon dataset\""],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9IbkHZ8tBlp6","executionInfo":{"status":"ok","timestamp":1725873920219,"user_tz":-420,"elapsed":367,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"fc1ea829-7869-4120-f87e-62cfb582d52f"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[main a8a757b] feat: run baseline on hackathon dataset\n"," 1 file changed, 1 insertion(+)\n"," create mode 100644 run_baseline_hackathon.ipynb\n"]}]},{"cell_type":"code","source":["from google.colab import userdata\n","repo_pat = userdata.get('ViNLU_github')\n","# repo_pat"],"metadata":{"id":"6EOrMma2ByqB"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!git remote set-url origin https://phongtintruong:@github.com/phongtintruong/ViNLU.git\n"],"metadata":{"id":"Szx9VtBLCTkF"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!git status"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rSGWoSBDFDtG","executionInfo":{"status":"ok","timestamp":1725873929000,"user_tz":-420,"elapsed":369,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"6551081b-c550-4194-a0bb-5424a8c08158"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["On branch main\n","Your branch is ahead of 'origin/main' by 1 commit.\n","  (use \"git push\" to publish your local commits)\n","\n","Untracked files:\n","  (use \"git add <file>...\" to include in what will be committed)\n","\t\u001b[31mHackathon/cached_dev_word-level_phobert-base_50\u001b[m\n","\t\u001b[31mHackathon/cached_test_word-level_phobert-base_50\u001b[m\n","\t\u001b[31mHackathon/cached_train_word-level_phobert-base_50\u001b[m\n","\n","nothing added to commit but untracked files present (use \"git add\" to track)\n"]}]},{"cell_type":"code","source":["!git push origin main"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"zUBAgpEpCeX-","executionInfo":{"status":"ok","timestamp":1725873934476,"user_tz":-420,"elapsed":1080,"user":{"displayName":"Thành Trung Nguyễn","userId":"00541940934395650104"}},"outputId":"f39faee6-12c6-4a38-93d0-80735fad8c61"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Enumerating objects: 4, done.\n","Counting objects:  25% (1/4)\rCounting objects:  50% (2/4)\rCounting objects:  75% (3/4)\rCounting objects: 100% (4/4)\rCounting objects: 100% (4/4), done.\n","Delta compression using up to 2 threads\n","Compressing objects:  33% (1/3)\rCompressing objects:  66% (2/3)\rCompressing objects: 100% (3/3)\rCompressing objects: 100% (3/3), done.\n","Writing objects:  33% (1/3)\rWriting objects:  66% (2/3)\rWriting objects: 100% (3/3)\rWriting objects: 100% (3/3), 17.72 KiB | 3.54 MiB/s, done.\n","Total 3 (delta 1), reused 0 (delta 0), pack-reused 0\n","remote: Resolving deltas: 100% (1/1), completed with 1 local object.\u001b[K\n","To https://github.com/phongtintruong/ViNLU.git\n","   3755e6c..a8a757b  main -> main\n"]}]}]}