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Bert Model","metadata":{"id":"TosIttxWKwkD"}},{"cell_type":"code","source":"pip install -q transformers datasets accelerate evaluate","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Imports","metadata":{"id":"90iYsVVAKuaJ"}},{"cell_type":"code","source":"import torch\nimport transformers\nimport datasets\n\nprint(\"CUDA Available:\", torch.cuda.is_available())\nprint(\"GPU Count:\", torch.cuda.device_count())\n\nfor i in range(torch.cuda.device_count()):\n print(torch.cuda.get_device_name(i))\n\nprint(\"Transformers:\", transformers.__version__)\nprint(\"Datasets:\", datasets.__version__)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:51:46.991953Z","iopub.execute_input":"2026-07-30T05:51:46.992649Z","iopub.status.idle":"2026-07-30T05:52:03.003963Z","shell.execute_reply.started":"2026-07-30T05:51:46.992606Z","shell.execute_reply":"2026-07-30T05:52:03.003109Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\nimport pickle\nimport time\nimport numpy as np\nimport pandas as pd\nimport joblib\n\nfrom sklearn.metrics import (\n accuracy_score,\n precision_score,\n recall_score,\n f1_score,\n roc_auc_score,\n confusion_matrix,\n classification_report\n)\nimport torch\nfrom transformers import (\n AutoTokenizer,\n AutoModelForSequenceClassification,\n TrainingArguments,\n Trainer,\n DataCollatorWithPadding\n)\nfrom datasets import Dataset\nfrom sklearn.metrics import accuracy_score, precision_recall_fscore_support","metadata":{"id":"jvfzMZ7JKijp","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:52:24.017553Z","iopub.execute_input":"2026-07-30T05:52:24.018029Z","iopub.status.idle":"2026-07-30T05:52:30.853897Z","shell.execute_reply.started":"2026-07-30T05:52:24.018004Z","shell.execute_reply":"2026-07-30T05:52:30.853068Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\nprint(\"Device: \", device)\n\nif torch.cuda.is_available():\n print(torch.cuda.get_device_name(0))","metadata":{"id":"Gcm7RSFLKihO","outputId":"39ae1236-cf43-4a74-f042-2c87cb9dda6b","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:52:33.441572Z","iopub.execute_input":"2026-07-30T05:52:33.442643Z","iopub.status.idle":"2026-07-30T05:52:33.448026Z","shell.execute_reply.started":"2026-07-30T05:52:33.442615Z","shell.execute_reply":"2026-07-30T05:52:33.447039Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Data","metadata":{"id":"MYAjivz8bvt0"}},{"cell_type":"code","source":"x_train = joblib.load(\"/kaggle/input/datasets/sudheermuthyala8688/data12/x_train.pkl\")\nx_test = joblib.load(\"/kaggle/input/datasets/sudheermuthyala8688/data12/x_test.pkl\")\n\ny_train = joblib.load(\"/kaggle/input/datasets/sudheermuthyala8688/data12/y_train.pkl\")\ny_test = joblib.load(\"/kaggle/input/datasets/sudheermuthyala8688/data12/y_test.pkl\")","metadata":{"id":"3iO4sxRIMR0Q","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:53:12.567692Z","iopub.execute_input":"2026-07-30T05:53:12.568551Z","iopub.status.idle":"2026-07-30T05:53:15.268677Z","shell.execute_reply.started":"2026-07-30T05:53:12.568515Z","shell.execute_reply":"2026-07-30T05:53:15.267781Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(type(x_train))\nprint(type(y_train))\n\nprint(len(x_train))\nprint(len(x_test))\n\nprint(x_train[:3])\nprint(y_train[:3])","metadata":{"id":"0DWgjUbKKicG","outputId":"c74e437f-05f5-43b5-95b9-9584a4844fba","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:53:16.776605Z","iopub.execute_input":"2026-07-30T05:53:16.777482Z","iopub.status.idle":"2026-07-30T05:53:16.784911Z","shell.execute_reply.started":"2026-07-30T05:53:16.777440Z","shell.execute_reply":"2026-07-30T05:53:16.784102Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Convert to Hugging Face Dataset","metadata":{"id":"7OrdRQRKOVqw"}},{"cell_type":"code","source":"tr_df = pd.DataFrame(\n {\n \"text\" : x_train,\n \"label\": y_train\n }\n)\n\nte_df = pd.DataFrame(\n {\n \"text\" : x_test,\n \"label\": y_test\n }\n)\nprint(tr_df.head())","metadata":{"id":"2CWsAs4QKiZF","outputId":"b4608259-7a9f-4dbc-fe44-3f8633d248de","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:15.038549Z","iopub.execute_input":"2026-07-30T05:55:15.038853Z","iopub.status.idle":"2026-07-30T05:55:15.088933Z","shell.execute_reply.started":"2026-07-30T05:55:15.038830Z","shell.execute_reply":"2026-07-30T05:55:15.088166Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_data = Dataset.from_pandas(tr_df)\ntest_data = Dataset.from_pandas(te_df)\nprint(train_data)\nprint(test_data)","metadata":{"id":"Q5l4nuBZKiWU","outputId":"82a4c69c-ebac-4c96-c5a4-dbdcf3648884","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:18.337089Z","iopub.execute_input":"2026-07-30T05:55:18.337533Z","iopub.status.idle":"2026-07-30T05:55:19.110992Z","shell.execute_reply.started":"2026-07-30T05:55:18.337505Z","shell.execute_reply":"2026-07-30T05:55:19.110200Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"a3WBHNoXKiTc","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"For your first BERT experiment, don't train on all 1.27 million tweets. It will take several hours on a T4 GPU.","metadata":{"id":"sUzLPh-UPVQL"}},{"cell_type":"code","source":"train_df = tr_df.sample(\n n=100000,\n random_state=42\n).reset_index(drop=True)\n\ntest_df = te_df.sample(\n n=25000,\n random_state=42\n).reset_index(drop=True)","metadata":{"id":"02Sa_gPOKiQ8","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:22.472930Z","iopub.execute_input":"2026-07-30T05:55:22.473356Z","iopub.status.idle":"2026-07-30T05:55:22.532351Z","shell.execute_reply.started":"2026-07-30T05:55:22.473326Z","shell.execute_reply":"2026-07-30T05:55:22.531737Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_dataset = Dataset.from_pandas(train_df)\ntest_dataset = Dataset.from_pandas(test_df)\n\nprint(train_dataset)\nprint(test_dataset)","metadata":{"id":"kelaIhSWKiOS","outputId":"eb9bf26b-9349-4662-cba0-93f7416815bb","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:23.198185Z","iopub.execute_input":"2026-07-30T05:55:23.199076Z","iopub.status.idle":"2026-07-30T05:55:23.277340Z","shell.execute_reply.started":"2026-07-30T05:55:23.199028Z","shell.execute_reply":"2026-07-30T05:55:23.276471Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"qWFBc5dvKiLu","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Tokenizer","metadata":{"id":"D92QoMA1P17R"}},{"cell_type":"code","source":"MODEL_NAME = \"bert-base-uncased\"","metadata":{"id":"5bVlfzt8KiJP","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:25.999766Z","iopub.execute_input":"2026-07-30T05:55:26.000187Z","iopub.status.idle":"2026-07-30T05:55:26.004213Z","shell.execute_reply.started":"2026-07-30T05:55:26.000159Z","shell.execute_reply":"2026-07-30T05:55:26.003477Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"bert_tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)","metadata":{"id":"jT-JDHqMKiGb","outputId":"2e0be608-dcca-4639-9559-e4ddbbd5a061","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:27.439738Z","iopub.execute_input":"2026-07-30T05:55:27.440764Z","iopub.status.idle":"2026-07-30T05:55:31.173710Z","shell.execute_reply.started":"2026-07-30T05:55:27.440717Z","shell.execute_reply":"2026-07-30T05:55:31.172782Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"MAX_LENGTH = 64\n\ndef tokenize_function(batch):\n return bert_tokenizer(\n batch[\"text\"],\n padding=\"max_length\",\n truncation=True,\n max_length=MAX_LENGTH\n )","metadata":{"id":"YrYZhFNyKiBY","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:31.175120Z","iopub.execute_input":"2026-07-30T05:55:31.175665Z","iopub.status.idle":"2026-07-30T05:55:31.180281Z","shell.execute_reply.started":"2026-07-30T05:55:31.175637Z","shell.execute_reply":"2026-07-30T05:55:31.179476Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(bert_tokenizer)\nprint(type(bert_tokenizer))","metadata":{"id":"lKrQqSFRRhZ1","outputId":"2946182d-9db0-42a1-d0af-f0f50b92ecda","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:34.836919Z","iopub.execute_input":"2026-07-30T05:55:34.837825Z","iopub.status.idle":"2026-07-30T05:55:34.842560Z","shell.execute_reply.started":"2026-07-30T05:55:34.837781Z","shell.execute_reply":"2026-07-30T05:55:34.841773Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_dataset = train_dataset.map(\n tokenize_function,\n batched=True,\n batch_size=1000\n )\n\ntest_dataset = test_dataset.map(\n tokenize_function,\n batched=True,\n batch_size=1000\n )","metadata":{"id":"E_cxGp5AKh-5","outputId":"d45b5fce-adbb-46d6-fa91-48ee5ff29d9b","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:45.127121Z","iopub.execute_input":"2026-07-30T05:55:45.127729Z","iopub.status.idle":"2026-07-30T05:55:51.862685Z","shell.execute_reply.started":"2026-07-30T05:55:45.127697Z","shell.execute_reply":"2026-07-30T05:55:51.861797Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_dataset = train_dataset.remove_columns([\"text\"])\ntest_dataset = test_dataset.remove_columns([\"text\"])\n\nif \"__index_level_0__\" in train_dataset.column_names:\n train_dataset = train_dataset.remove_columns([\"__index_level_0__\"])\n test_dataset = test_dataset.remove_columns([\"__index_level_0__\"])","metadata":{"id":"BuVPreP-Kh8c","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:56.552018Z","iopub.execute_input":"2026-07-30T05:55:56.552464Z","iopub.status.idle":"2026-07-30T05:55:56.560531Z","shell.execute_reply.started":"2026-07-30T05:55:56.552425Z","shell.execute_reply":"2026-07-30T05:55:56.559923Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Rename Label Column","metadata":{"id":"dYuvzE9mSW15"}},{"cell_type":"code","source":"train_dataset = train_dataset.rename_column(\"label\", \"labels\")\ntest_dataset = test_dataset.rename_column(\"label\", \"labels\")","metadata":{"id":"yMpjo5LoKh6F","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:55:59.448111Z","iopub.execute_input":"2026-07-30T05:55:59.448567Z","iopub.status.idle":"2026-07-30T05:55:59.456190Z","shell.execute_reply.started":"2026-07-30T05:55:59.448538Z","shell.execute_reply":"2026-07-30T05:55:59.455363Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Convert to PyTorch Format","metadata":{"id":"Q-RqzeVQSaJ0"}},{"cell_type":"code","source":"train_dataset.set_format(\n type=\"torch\",\n columns=[\n \"input_ids\",\n \"attention_mask\",\n \"labels\"\n ]\n)\n\ntest_dataset.set_format(\n type=\"torch\",\n columns=[\n \"input_ids\",\n \"attention_mask\",\n \"labels\"\n ]\n)","metadata":{"id":"_guFZAyWKh39","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:56:01.489155Z","iopub.execute_input":"2026-07-30T05:56:01.489911Z","iopub.status.idle":"2026-07-30T05:56:01.495444Z","shell.execute_reply.started":"2026-07-30T05:56:01.489880Z","shell.execute_reply":"2026-07-30T05:56:01.494417Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(train_dataset)\nprint(train_dataset[0])","metadata":{"id":"oD5V87_6Kh1L","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:56:09.417612Z","iopub.execute_input":"2026-07-30T05:56:09.417980Z","iopub.status.idle":"2026-07-30T05:56:09.458891Z","shell.execute_reply.started":"2026-07-30T05:56:09.417952Z","shell.execute_reply":"2026-07-30T05:56:09.458220Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"CbV-AarZKhye","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Model","metadata":{"id":"zslgkra8YW8Z"}},{"cell_type":"code","source":"model = AutoModelForSequenceClassification.from_pretrained(\n \"bert-base-uncased\",\n num_labels=2\n)","metadata":{"id":"Tt5jEmtZKhwD","outputId":"59477930-ba06-4a1e-997c-12a1b252d606","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:03.084245Z","iopub.execute_input":"2026-07-30T05:57:03.085023Z","iopub.status.idle":"2026-07-30T05:57:03.838128Z","shell.execute_reply.started":"2026-07-30T05:57:03.084990Z","shell.execute_reply":"2026-07-30T05:57:03.833093Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"ZHphIXcTKhtr","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Training Arguments","metadata":{"id":"OAEdyBfzYx3g"}},{"cell_type":"code","source":"train_args = TrainingArguments(\n output_dir=\"./bert_results\",\n eval_strategy=\"epoch\",\n save_strategy=\"epoch\",\n\n learning_rate=2e-5,\n per_device_train_batch_size=16,\n per_device_eval_batch_size=32,\n\n num_train_epochs=3,\n weight_decay=0.01,\n logging_steps=100,\n\n load_best_model_at_end=True,\n metric_for_best_model=\"accuracy\",\n greater_is_better=True,\n\n fp16=True,\n report_to=\"none\"\n)","metadata":{"id":"LmaziKJtKhrW","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:09.746303Z","iopub.execute_input":"2026-07-30T05:57:09.746836Z","iopub.status.idle":"2026-07-30T05:57:10.024501Z","shell.execute_reply.started":"2026-07-30T05:57:09.746808Z","shell.execute_reply":"2026-07-30T05:57:10.023830Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"Lo3c9Bwtbi-a","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Data Collator","metadata":{"id":"PX3yXiQCbjir"}},{"cell_type":"code","source":"data_collator = DataCollatorWithPadding(\n tokenizer=bert_tokenizer\n)","metadata":{"id":"7I9xdNDjbi6r","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:18.184601Z","iopub.execute_input":"2026-07-30T05:57:18.184866Z","iopub.status.idle":"2026-07-30T05:57:18.189161Z","shell.execute_reply.started":"2026-07-30T05:57:18.184844Z","shell.execute_reply":"2026-07-30T05:57:18.188249Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"M1H7cdgSbi25","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Metrics","metadata":{"id":"bPrsJgR2boEx"}},{"cell_type":"code","source":"def compute_metrics(eval_pred):\n logits, labels = eval_pred\n predictions = np.argmax(logits, axis=1)\n\n precision, recall, f1, _ = precision_recall_fscore_support(\n labels,\n predictions,\n average=\"binary\"\n )\n accuracy = accuracy_score(labels, predictions)\n\n return {\n \"accuracy\": accuracy,\n \"precision\": precision,\n \"recall\": recall,\n \"f1\": f1\n }","metadata":{"id":"K83AIZJLKhpO","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:20.477063Z","iopub.execute_input":"2026-07-30T05:57:20.477656Z","iopub.status.idle":"2026-07-30T05:57:20.482291Z","shell.execute_reply.started":"2026-07-30T05:57:20.477626Z","shell.execute_reply":"2026-07-30T05:57:20.481604Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"Create the Trainer","metadata":{"id":"IRlZjcN4alqj"}},{"cell_type":"code","source":"trainer = Trainer(\n model=model,\n args=train_args,\n train_dataset=train_dataset,\n eval_dataset=test_dataset,\n data_collator=data_collator,\n compute_metrics=compute_metrics,\n processing_class=bert_tokenizer\n)","metadata":{"id":"EmodkJkAKhmR","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:25.397102Z","iopub.execute_input":"2026-07-30T05:57:25.397964Z","iopub.status.idle":"2026-07-30T05:57:25.565677Z","shell.execute_reply.started":"2026-07-30T05:57:25.397920Z","shell.execute_reply":"2026-07-30T05:57:25.564721Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"Pg6jZeEUKhjs","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import torch\nimport torchvision\nimport datasets\nimport transformers\n\nprint(\"Torch:\", torch.__version__)\nprint(\"Torchvision:\", torchvision.__version__)\nprint(\"Datasets:\", datasets.__version__)\nprint(\"Transformers:\", transformers.__version__)","metadata":{"id":"FohFY7KHctXe","outputId":"60007d63-e807-4cdb-d385-6c31589385fb","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:26.480794Z","iopub.execute_input":"2026-07-30T05:57:26.481383Z","iopub.status.idle":"2026-07-30T05:57:26.487534Z","shell.execute_reply.started":"2026-07-30T05:57:26.481345Z","shell.execute_reply":"2026-07-30T05:57:26.486752Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import time\nstart_time = time.time()\ntrainer.train()\nend_time = time.time()\n\nprint(f\"Training Time: {(end_time - start_time) / 60:.2f} minutes\")","metadata":{"id":"pwStuBiDKhhG","outputId":"c82e8760-6329-437b-c394-64777a598d98","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T05:57:28.262584Z","iopub.execute_input":"2026-07-30T05:57:28.263330Z","iopub.status.idle":"2026-07-30T06:45:11.229563Z","shell.execute_reply.started":"2026-07-30T05:57:28.263298Z","shell.execute_reply":"2026-07-30T06:45:11.228711Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"results = trainer.evaluate()\nprint(results)","metadata":{"id":"jBvDypJVKhe7","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T06:50:35.362011Z","iopub.execute_input":"2026-07-30T06:50:35.362893Z","iopub.status.idle":"2026-07-30T06:51:39.613571Z","shell.execute_reply.started":"2026-07-30T06:50:35.362857Z","shell.execute_reply":"2026-07-30T06:51:39.612794Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import json\n\nevaluation_results = {\n \"Evaluation Loss\": 0.8950701355934143,\n \"Accuracy\": 0.79936,\n \"Precision\": 0.8124226676565207,\n \"Recall\": 0.7822253990945913,\n \"F1 Score\": 0.7970381160475843,\n \"Evaluation Runtime\": 64.2416,\n \"Samples per Second\": 389.156,\n \"Steps per Second\": 6.086\n}\n\nwith open(\"bert_evaluation_results.json\", \"w\") as f:\n json.dump(evaluation_results, f, indent=4)\n\nprint(\"Evaluation results saved successfully.\")","metadata":{"id":"zH8wRdDQKhcG","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T06:57:29.254580Z","iopub.execute_input":"2026-07-30T06:57:29.255003Z","iopub.status.idle":"2026-07-30T06:57:29.260926Z","shell.execute_reply.started":"2026-07-30T06:57:29.254975Z","shell.execute_reply":"2026-07-30T06:57:29.260297Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"trainer.save_model(\"bert_sentiment_model\")\nbert_tokenizer.save_pretrained(\"bert_sentiment_model\")\n\nprint(\"BERT model saved successfully!\")","metadata":{"id":"g7ikzLH7KhZh","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import shutil\n\nshutil.make_archive(\"bert_sentiment_model\", \"zip\", \"bert_sentiment_model\")\n\nprint(\"ZIP file created successfully!\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-07-30T07:01:42.348501Z","iopub.execute_input":"2026-07-30T07:01:42.348866Z","iopub.status.idle":"2026-07-30T07:02:06.033840Z","shell.execute_reply.started":"2026-07-30T07:01:42.348839Z","shell.execute_reply":"2026-07-30T07:02:06.033140Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import numpy as np\nfrom sklearn.metrics import classification_report\n\npredictions = trainer.predict(test_dataset)\n\ny_pred = np.argmax(predictions.predictions, axis=1)\ny_true = predictions.label_ids\n\nprint(classification_report(y_true, y_pred))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-07-30T07:00:37.380079Z","iopub.execute_input":"2026-07-30T07:00:37.380889Z","iopub.status.idle":"2026-07-30T07:01:42.347032Z","shell.execute_reply.started":"2026-07-30T07:00:37.380855Z","shell.execute_reply":"2026-07-30T07:01:42.346057Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\nimport matplotlib.pyplot as plt\n\ncm = confusion_matrix(y_true, y_pred)\n\ndisp = ConfusionMatrixDisplay(\n confusion_matrix=cm,\n display_labels=[\"Negative\", \"Positive\"]\n)\n\ndisp.plot(cmap=\"Blues\")\nplt.title(\"BERT Confusion Matrix\")\nplt.show()","metadata":{"id":"iK4my5qQKhW9","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T07:03:44.738705Z","iopub.execute_input":"2026-07-30T07:03:44.739172Z","iopub.status.idle":"2026-07-30T07:03:44.928504Z","shell.execute_reply.started":"2026-07-30T07:03:44.739142Z","shell.execute_reply":"2026-07-30T07:03:44.927686Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"from transformers import pipeline\n\nclassifier = pipeline(\n \"sentiment-analysis\",\n model=\"bert_sentiment_model\",\n tokenizer=\"bert_sentiment_model\"\n)\n\ntexts = [\n \"I love this movie!\",\n \"This is the worst experience ever.\",\n \"The service was average.\"\n]\n\nfor text in texts:\n result = classifier(text)\n print(text)\n print(result)\n print(\"-\" * 50)","metadata":{"id":"gcj0s8JYKhUl","trusted":true,"execution":{"iopub.status.busy":"2026-07-30T07:04:02.906181Z","iopub.execute_input":"2026-07-30T07:04:02.907050Z","iopub.status.idle":"2026-07-30T07:04:04.244128Z","shell.execute_reply.started":"2026-07-30T07:04:02.907007Z","shell.execute_reply":"2026-07-30T07:04:04.243264Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"hOOarmOMKhRq","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"lYCi5lLxKhLR","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"b30tD0X2KhIi","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"hgHky9fJKhGK","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"QJXMQ4kRKhDr","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"3PgBLcNgKhA6","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"Ue_fYERTKg98","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"id":"zB28cbemKg7J","trusted":true},"outputs":[],"execution_count":null}]} |