run_albert.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"accelerator":"GPU","colab":{"name":"run_albert.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.11"},"varInspector":{"cols":{"lenName":16,"lenType":16,"lenVar":40},"kernels_config":{"python":{"delete_cmd_postfix":"","delete_cmd_prefix":"del ","library":"var_list.py","varRefreshCmd":"print(var_dic_list())"},"r":{"delete_cmd_postfix":") ","delete_cmd_prefix":"rm(","library":"var_list.r","varRefreshCmd":"cat(var_dic_list()) "}},"types_to_exclude":["module","function","builtin_function_or_method","instance","_Feature"],"window_display":false}},"cells":[{"cell_type":"markdown","metadata":{"id":"HJhco21g8EBQ"},"source":["# This notebook is recommended to run in Google Colab, where you may use free GPU resources."]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ar4O_1tszb8L","executionInfo":{"elapsed":1067,"status":"ok","timestamp":1604855426321,"user":{"displayName":"Yuxin JIANG","photoUrl":"","userId":"08237551511886881536"},"user_tz":-480},"outputId":"3ab19084-cc8b-4592-9e67-4d5cab7e1dec"},"source":["from google.colab import drive\n","drive.mount('/content/drive/')"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Drive already mounted at /content/drive/; to attempt to forcibly remount, call drive.mount(\"/content/drive/\", force_remount=True).\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5mmqSh3szedt","executionInfo":{"elapsed":6183,"status":"ok","timestamp":1604855431443,"user":{"displayName":"Yuxin JIANG","photoUrl":"","userId":"08237551511886881536"},"user_tz":-480},"outputId":"d87c0ae9-b37c-4feb-dd98-20db616bbc72"},"source":["! pip3 install transformers"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: transformers in /usr/local/lib/python3.6/dist-packages (3.4.0)\n","Requirement already satisfied: dataclasses; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from transformers) (0.7)\n","Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from transformers) (2.23.0)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.6/dist-packages (from transformers) (2019.12.20)\n","Requirement already satisfied: sentencepiece!=0.1.92 in /usr/local/lib/python3.6/dist-packages (from transformers) (0.1.94)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.6/dist-packages (from transformers) (4.41.1)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.6/dist-packages (from transformers) (3.0.12)\n","Requirement already satisfied: sacremoses in /usr/local/lib/python3.6/dist-packages (from transformers) (0.0.43)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from transformers) (1.18.5)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.6/dist-packages (from transformers) (20.4)\n","Requirement already satisfied: tokenizers==0.9.2 in /usr/local/lib/python3.6/dist-packages (from transformers) (0.9.2)\n","Requirement already satisfied: protobuf in /usr/local/lib/python3.6/dist-packages (from transformers) (3.12.4)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2.10)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (1.24.3)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (3.0.4)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->transformers) (2020.6.20)\n","Requirement already satisfied: click in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (7.1.2)\n","Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (1.15.0)\n","Requirement already satisfied: joblib in /usr/local/lib/python3.6/dist-packages (from sacremoses->transformers) (0.17.0)\n","Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.6/dist-packages (from packaging->transformers) (2.4.7)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf->transformers) (50.3.2)\n","Requirement already satisfied: jsonlines in /usr/local/lib/python3.6/dist-packages (1.2.0)\n","Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from jsonlines) (1.15.0)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"a0Yf9E5vzfsU","executionInfo":{"elapsed":859,"status":"ok","timestamp":1604855434102,"user":{"displayName":"Yuxin JIANG","photoUrl":"","userId":"08237551511886881536"},"user_tz":-480},"outputId":"20d68ebf-87fb-4125-e284-331b217210cd"},"source":["%cd /content/drive/My Drive/SST-2-sentiment-analysis/"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/content/drive/My Drive/LCQMC/BERTs\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"4gOaY35AqVa-"},"source":["## SST-2 train-validate-test"]},{"cell_type":"code","metadata":{"id":"XNDyLJErqdij"},"source":["from run_Albert_model import model_train_validate_test\n","import pandas as pd\n","from utils import Metric\n","import os\n","\n","data_path = \"/content/drive/My Drive/SST-2-sentiment-analysis/data/\"\n","train_df = pd.read_csv(os.path.join(data_path,\"train.tsv\"),sep='\\t',header=None, names=['similarity','s1'])\n","dev_df = pd.read_csv(os.path.join(data_path,\"dev.tsv\"),sep='\\t',header=None, names=['similarity','s1'])\n","test_df = pd.read_csv(os.path.join(data_path,\"test.tsv\"),sep='\\t',header=None, names=['similarity','s1'])\n","target_dir = \"/content/drive/My Drive/SST-2-sentiment-analysis/output/Albert/\"\n","\n","model_train_validate_test(train_df, dev_df, test_df, target_dir, \n","         max_seq_len=50,\n","         epochs=3,\n","         batch_size=32,\n","         lr=2e-05,\n","         patience=1,\n","         max_grad_norm=10.0,\n","         if_save_model=True,\n","         checkpoint=None)\n","\n","test_result = pd.read_csv(os.path.join(target_dir, 'test_prediction.csv'))\n","Metric(test_df.similarity, test_result.prediction) "],"execution_count":null,"outputs":[]}]}