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andyqin18 commited on
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1 Parent(s): bcfb40b

Commented finetune.ipynb

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Files changed (4) hide show
  1. app.py +1 -1
  2. milestone3/.ipynb_checkpoints/finetune-checkpoint.ipynb +0 -0
  3. milestone3/finetune.ipynb +0 -0
  4. milestone3/finetune_notebook.ipynb +0 -1236
app.py CHANGED
@@ -4,7 +4,7 @@ import numpy as np
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  from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
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  # Define global variables
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- FINE_TUNED_MODEL = "andyqin18/test-finetuned"
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  NUM_SAMPLE_TEXT = 10
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  # Define analyze function
 
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  from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
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  # Define global variables
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+ FINE_TUNED_MODEL = "andyqin18/finetuned-bert-uncased"
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  NUM_SAMPLE_TEXT = 10
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  # Define analyze function
milestone3/.ipynb_checkpoints/finetune-checkpoint.ipynb ADDED
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milestone3/finetune.ipynb ADDED
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milestone3/finetune_notebook.ipynb DELETED
@@ -1,1236 +0,0 @@
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- "value": "<center> <img\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.svg\nalt='Hugging Face'> <br> Copy a token from <a\nhref=\"https://huggingface.co/settings/tokens\" target=\"_blank\">your Hugging Face\ntokens page</a> and paste it below. <br> Immediately click login after copying\nyour token or it might be stored in plain text in this notebook file. </center>"
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898
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901
- "base_uri": "https://localhost:8080/"
902
- },
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- {
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- "text": [
912
- "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
913
- "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.28.1)\n",
914
- "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.0)\n",
915
- "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.22.4)\n",
916
- "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.65.0)\n",
917
- "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.27.1)\n",
918
- "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.13.3)\n",
919
- "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2022.10.31)\n",
920
- "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.14.1)\n",
921
- "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
922
- "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0)\n",
923
- "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.5.0)\n",
924
- "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (2023.4.0)\n",
925
- "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
926
- "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.15)\n",
927
- "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2022.12.7)\n",
928
- "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.12)\n"
929
- ]
930
- }
931
- ]
932
- },
933
- {
934
- "cell_type": "markdown",
935
- "source": [
936
- "---------------------------------------------------------"
937
- ],
938
- "metadata": {
939
- "id": "AYvuPa35Wq9C"
940
- }
941
- },
942
- {
943
- "cell_type": "code",
944
- "source": [
945
- "import pandas as pd\n",
946
- "import numpy as np\n",
947
- "import torch\n",
948
- "from sklearn.model_selection import train_test_split\n",
949
- "from torch.utils.data import Dataset\n",
950
- "from transformers import AutoTokenizer, AutoModelForSequenceClassification, TrainingArguments, Trainer\n",
951
- "device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')\n"
952
- ],
953
- "metadata": {
954
- "id": "hQN-HmXXW6SA"
955
- },
956
- "execution_count": null,
957
- "outputs": []
958
- },
959
- {
960
- "cell_type": "code",
961
- "source": [
962
- "df = pd.read_csv(\"/content/drive/MyDrive/AI_project/data/train.csv\")\n",
963
- "\n",
964
- "train_texts = df[\"comment_text\"].values\n",
965
- "labels = df.columns[2:]\n",
966
- "id2label = {idx:label for idx, label in enumerate(labels)}\n",
967
- "label2id = {label:idx for idx, label in enumerate(labels)}\n",
968
- "train_labels = df[labels].values\n",
969
- "# print(train_labels[0])\n",
970
- "\n",
971
- "\n",
972
- "\n",
973
- "np.random.seed(18)\n",
974
- "small_train_texts = np.random.choice(train_texts, size=30000, replace=False)\n",
975
- "\n",
976
- "np.random.seed(18)\n",
977
- "small_train_labels_idx = np.random.choice(train_labels.shape[0], size=30000, replace=False)\n",
978
- "small_train_labels = train_labels[small_train_labels_idx, :]\n",
979
- "# print(small_train_texts,small_train_labels)\n",
980
- "\n",
981
- "\n",
982
- "train_texts, val_texts, train_labels, val_labels = train_test_split(small_train_texts, small_train_labels, test_size=.2)\n",
983
- "# train_texts, val_texts, train_labels, val_labels = train_test_split(train_texts, train_labels, test_size=.2)"
984
- ],
985
- "metadata": {
986
- "id": "WtsAFyrzWuCr"
987
- },
988
- "execution_count": null,
989
- "outputs": []
990
- },
991
- {
992
- "cell_type": "code",
993
- "source": [
994
- "tokenizer = AutoTokenizer.from_pretrained(\"bert-base-uncased\")\n",
995
- "#Set up the dataset\n",
996
- "# train_encodings = tokenizer(train_texts, truncation=True, padding=True)\n",
997
- "# val_encodings = tokenizer(val_texts, truncation=True, padding=True)"
998
- ],
999
- "metadata": {
1000
- "id": "pPgvgOaYXb2f"
1001
- },
1002
- "execution_count": null,
1003
- "outputs": []
1004
- },
1005
- {
1006
- "cell_type": "code",
1007
- "source": [
1008
- "class TextDataset(Dataset):\n",
1009
- " def __init__(self,texts,labels):\n",
1010
- " self.texts = texts\n",
1011
- " self.labels = labels\n",
1012
- "\n",
1013
- " def __getitem__(self,idx):\n",
1014
- " encodings = tokenizer(self.texts[idx], truncation=True, padding=\"max_length\")\n",
1015
- " item = {key: torch.tensor(val) for key, val in encodings.items()}\n",
1016
- " item['labels'] = torch.tensor(self.labels[idx],dtype=torch.float32)\n",
1017
- " del encodings\n",
1018
- " return item\n",
1019
- "\n",
1020
- " def __len__(self):\n",
1021
- " return len(self.labels)\n",
1022
- "\n"
1023
- ],
1024
- "metadata": {
1025
- "id": "aysAKCYoXBoz"
1026
- },
1027
- "execution_count": null,
1028
- "outputs": []
1029
- },
1030
- {
1031
- "cell_type": "code",
1032
- "source": [
1033
- "from huggingface_hub import notebook_login\n",
1034
- "\n",
1035
- "notebook_login()"
1036
- ],
1037
- "metadata": {
1038
- "colab": {
1039
- "base_uri": "https://localhost:8080/",
1040
- "height": 113,
1041
- "referenced_widgets": [
1042
- "5777416c505a42619da32a0cb9707d82",
1043
- "9e6e8abf4d324a7b8535172edbd7c954",
1044
- "1315624eb80a4517b79d814770cbe189",
1045
- "7ec85b07ed1b4fccbab20a3b3183b173",
1046
- "00aad7e6e5404b2f8f43182d660698ae",
1047
- "2182e718553d4959bfffc2ef5aa24d53",
1048
- "98572cb68e274cb99844efa8a661f668",
1049
- "1ed2e107cb794dc7923089751ac41dc3",
1050
- "29e71af41da9418db9aaf3a08e3e7d21",
1051
- "1f7be06c638148d5b11ecee631598e26",
1052
- "ee9944452aee42d1bd04de0986249c08",
1053
- "95a9fb94616a4c07b1c2e167a876c3fc",
1054
- "435f1dfcc2264876a2ef31a634abc13a",
1055
- "da38a43d5848415280acf6bcc8408d9f",
1056
- "c0fcb22e27f64aeda77cdb31ba1dbc21",
1057
- "5f35bbd6fb9f4c7babb294a1cdb65cb6",
1058
- "d380510cfb9e40b09c98a16ad5c67f51",
1059
- "09cae48b80da40b39f358d1310f397c3",
1060
- "8cb9ff0be0904b459ffee0cdd91ecf53",
1061
- "6cae637442ac47be92792afefb5eca1b",
1062
- "40b2c027600349f6b026ed63ce056a99",
1063
- "c0b5b216c5de43d39a5653c6159727c1",
1064
- "dc816285a79147888b8558524148d042",
1065
- "ef039b61681e42d59db86fea20dd3019",
1066
- "7b110bf457514812b02fa2c20c57eb8b",
1067
- "40b166a8206a42e8982a8331fe38a13c",
1068
- "aad77133528e44f7831786c99f185ed3",
1069
- "c2178ad5d0c6491a8bdf9aaa8e840f84",
1070
- "290c727552a84c2fba378fcd448aae4f"
1071
- ]
1072
- },
1073
- "id": "BcZnYYII3Nxo",
1074
- "outputId": "16a4dc55-757f-4133-abb5-6e1f482c7e16"
1075
- },
1076
- "execution_count": null,
1077
- "outputs": [
1078
- {
1079
- "output_type": "display_data",
1080
- "data": {
1081
- "text/plain": [
1082
- "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
1083
- ],
1084
- "application/vnd.jupyter.widget-view+json": {
1085
- "version_major": 2,
1086
- "version_minor": 0,
1087
- "model_id": "5777416c505a42619da32a0cb9707d82"
1088
- }
1089
- },
1090
- "metadata": {}
1091
- }
1092
- ]
1093
- },
1094
- {
1095
- "cell_type": "code",
1096
- "source": [
1097
- "train_dataset = TextDataset(train_texts,train_labels)\n",
1098
- "val_dataset = TextDataset(val_texts, val_labels)\n",
1099
- "# small_train_dataset = train_dataset.shuffle(seed=42).select(range(1000))\n",
1100
- "# small_val_dataset = val_dataset.shuffle(seed=42).select(range(1000))\n",
1101
- "\n",
1102
- "\n",
1103
- "\n",
1104
- "# model = AutoModelForSequenceClassification.from_pretrained(\"bert-base-uncased\", num_labels=6, problem_type=\"multi_label_classification\")\n",
1105
- "\n",
1106
- "model = AutoModelForSequenceClassification.from_pretrained(\"bert-base-uncased\", \n",
1107
- " problem_type=\"multi_label_classification\", \n",
1108
- " num_labels=len(labels),\n",
1109
- " id2label=id2label,\n",
1110
- " label2id=label2id)\n",
1111
- "model.to(device)\n",
1112
- "\n",
1113
- "training_args = TrainingArguments(\n",
1114
- " output_dir=\"finetuned-bert-uncased\",\n",
1115
- " evaluation_strategy = \"epoch\",\n",
1116
- " save_strategy = \"epoch\",\n",
1117
- " learning_rate=2e-5,\n",
1118
- " per_device_train_batch_size=16,\n",
1119
- " per_device_eval_batch_size=16,\n",
1120
- " num_train_epochs=5,\n",
1121
- " load_best_model_at_end=True,\n",
1122
- " push_to_hub=True,\n",
1123
- ")\n",
1124
- "\n",
1125
- "trainer = Trainer(\n",
1126
- " model=model,\n",
1127
- " args=training_args,\n",
1128
- " train_dataset=train_dataset,\n",
1129
- " eval_dataset=val_dataset,\n",
1130
- " tokenizer=tokenizer\n",
1131
- ")\n",
1132
- "\n",
1133
- "trainer.train()"
1134
- ],
1135
- "metadata": {
1136
- "colab": {
1137
- "base_uri": "https://localhost:8080/",
1138
- "height": 320
1139
- },
1140
- "id": "BDptWdAAYs29",
1141
- "outputId": "c885d19a-5fb9-4fec-9468-550928037ba3"
1142
- },
1143
- "execution_count": null,
1144
- "outputs": [
1145
- {
1146
- "output_type": "stream",
1147
- "name": "stderr",
1148
- "text": [
1149
- "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForSequenceClassification: ['cls.predictions.decoder.weight', 'cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.bias', 'cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.LayerNorm.bias']\n",
1150
- "- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
1151
- "- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
1152
- "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.weight', 'classifier.bias']\n",
1153
- "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
1154
- "/content/finetuned-bert-uncased is already a clone of https://huggingface.co/andyqin18/finetuned-bert-uncased. Make sure you pull the latest changes with `repo.git_pull()`.\n",
1155
- "WARNING:huggingface_hub.repository:/content/finetuned-bert-uncased is already a clone of https://huggingface.co/andyqin18/finetuned-bert-uncased. Make sure you pull the latest changes with `repo.git_pull()`.\n",
1156
- "/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:391: 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",
1157
- " warnings.warn(\n",
1158
- "You're using a BertTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
1159
- ]
1160
- },
1161
- {
1162
- "output_type": "display_data",
1163
- "data": {
1164
- "text/plain": [
1165
- "<IPython.core.display.HTML object>"
1166
- ],
1167
- "text/html": [
1168
- "\n",
1169
- " <div>\n",
1170
- " \n",
1171
- " <progress value='3001' max='7500' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
1172
- " [3001/7500 1:16:16 < 1:54:24, 0.66 it/s, Epoch 2/5]\n",
1173
- " </div>\n",
1174
- " <table border=\"1\" class=\"dataframe\">\n",
1175
- " <thead>\n",
1176
- " <tr style=\"text-align: left;\">\n",
1177
- " <th>Epoch</th>\n",
1178
- " <th>Training Loss</th>\n",
1179
- " <th>Validation Loss</th>\n",
1180
- " </tr>\n",
1181
- " </thead>\n",
1182
- " <tbody>\n",
1183
- " <tr>\n",
1184
- " <td>1</td>\n",
1185
- " <td>0.048900</td>\n",
1186
- " <td>0.054034</td>\n",
1187
- " </tr>\n",
1188
- " </tbody>\n",
1189
- "</table><p>\n",
1190
- " <div>\n",
1191
- " \n",
1192
- " <progress value='273' max='375' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
1193
- " [273/375 02:25 < 00:54, 1.87 it/s]\n",
1194
- " </div>\n",
1195
- " "
1196
- ]
1197
- },
1198
- "metadata": {}
1199
- }
1200
- ]
1201
- },
1202
- {
1203
- "cell_type": "code",
1204
- "source": [
1205
- "# print(device)"
1206
- ],
1207
- "metadata": {
1208
- "id": "GH702kPdbbjs"
1209
- },
1210
- "execution_count": null,
1211
- "outputs": []
1212
- },
1213
- {
1214
- "cell_type": "code",
1215
- "source": [
1216
- "# trainer.push_to_hub()"
1217
- ],
1218
- "metadata": {
1219
- "id": "T-VyJbD_gMkx"
1220
- },
1221
- "execution_count": null,
1222
- "outputs": []
1223
- },
1224
- {
1225
- "cell_type": "code",
1226
- "source": [
1227
- "# tokenizer.push_to_hub(\"andyqin18/test-finetuned\")"
1228
- ],
1229
- "metadata": {
1230
- "id": "iIHPfQZfhQpN"
1231
- },
1232
- "execution_count": null,
1233
- "outputs": []
1234
- }
1235
- ]
1236
- }