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0: Installation of Packages"],"metadata":{"id":"uKPqSuAb3huQ"}},{"cell_type":"code","source":["!pip uninstall -y wandb     # avoid experiment tracking"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"vOj0CZIA-OoN","executionInfo":{"status":"ok","timestamp":1741180543982,"user_tz":-480,"elapsed":6926,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"c5002db5-05b3-4226-8fbd-0344c8f3193e"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Found existing installation: wandb 0.19.7\n","Uninstalling wandb-0.19.7:\n","  Successfully uninstalled wandb-0.19.7\n"]}]},{"cell_type":"code","source":["!pip install transformers[torch] -q\n","!pip install dataset -q\n","!pip install evaluate -q"],"metadata":{"id":"L7k1KWoLaTi8","executionInfo":{"status":"ok","timestamp":1741180664064,"user_tz":-480,"elapsed":120080,"user":{"displayName":"ISOM5240 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This behaviour is the source of the following dependency conflicts.\n","ipython-sql 0.5.0 requires sqlalchemy>=2.0, but you have sqlalchemy 1.4.54 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m84.0/84.0 kB\u001b[0m \u001b[31m7.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m485.4/485.4 kB\u001b[0m \u001b[31m30.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m11.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.5/143.5 kB\u001b[0m \u001b[31m13.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h"]}]},{"cell_type":"markdown","source":["#Step 1: Obtain your own dataset - yelp_review_full"],"metadata":{"id":"I9t9eckA3V42"}},{"cell_type":"code","execution_count":3,"metadata":{"id":"KMQ8w1CO9fp6","colab":{"base_uri":"https://localhost:8080/","height":318,"referenced_widgets":["24e80202ea134722b3e462798db290da","fe8b42f262784165b5e657e37bbf5d8f","ddef02952a5c416d889155f22aea4bad","e4bfd0bc6f2f4aa691c31b48f77f8c97","5bef8e8c7ab749fb83c6eb8a65166317","c9039ab6ab7149d4944fc60d4ce29555","0145b5eb22044830889cea2dee8fb19d","a30576991db643419915050a82d67225","b9c28112e82440eabe6bbfbdb8d33502","32606de1cf494507922939539833b314","16ee246faeb84265ae1137380b76d13e","062b5dbf71ff412fa5c169376f78bc31","4cfba508658745ddba6b475bebfc0ab8","fc918c116263434ab98b1457eac6bcb5","f8154fc5024f4ea8b5609d0aa422f92d","c36a11435b1a45738259cb6a9c8e9d5a","245143f9d3164f1c9cf7defd9db7dfc9","03dc4fa2068a4e5eac4b9b29953bf409","a4c24b38beb94ea49f503ab19cba89c7","a339cd9222c24fb9bba366915ce22ab1","c1a99fc5896447cab287b0fff994a366","3355c5e444944fbe86690f846ab28a70","f2773bd9eeb943a5b7335d9b144756fb","dd0baaa3fce44bdd8e69324b30eb01b7","cc0b51598e3147c88780a264f07022a7","23bedb581bde43c495d18645ddca2b61","66a21669f2594d9cb7d102aba71d613d","380006a391704eac86e1f25e80ea8efe","734ca973fae94039a39a4fa7c120120b","2ccfae6edb234634b1bb31376e28dd46","e4fc4f7bc6534f9ca64fb4c2b60c7581","48664e0a92684befa296ca46ef74693c","30b3a8259d534328bd10eb41d023dc63","25f9fa2bd7d7482f9958bd385cd36da1","0e58e47d9ee44df89cfbaf54e1664802","c7d37012b97a4497abb2d6554ce6e78e","db0ae760a92c4d0ea2fa083d15859c7b","e6da568c7fb4460f85b6492435c2fc1b","5c11b2cdb6b843c487b658dd578669f7","f1bb6de3b44f4f439fc6a7b1a866f613","3d0d6f94f7e54f74a7de48336de93854","8f74f9fe501241ef9e7cc168aad3e12e","18d2fa28399b40d081fe399ff3c433e7","574c4ec42b1343178f7a3d6758150b17","a1e3cfec50f1486487f184ad9b207f52","f30526551b2e4bef8b464c1ab6c8ea57","6ebc8aada3794ea9a084c0ebf3030872","abe9b1b48a9b44de89a23f10a8c59ae5","5449bea585e74b99baa8e0a0d274cd68","1c654e55d3884d40979428bc9baf1b01","25beb6211b594030bac32f5d65b59ffb","91101f52c1734604b5f8e6bb1b3c6eca","47246166e646490e8151f98125e41377","76a84ea94ad544ec9ae1e3e083cf39fc","5af7b64e127e49eb90c25d092b90473b"]},"executionInfo":{"status":"ok","timestamp":1741180691015,"user_tz":-480,"elapsed":26948,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"a91ef583-62b0-400e-ca28-52a6e06754a5"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n","The secret `HF_TOKEN` does not exist in your Colab secrets.\n","To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n","You will be able to reuse this secret in all of your notebooks.\n","Please note that authentication is recommended but still optional to access public models or datasets.\n","  warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["README.md:   0%|          | 0.00/6.72k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"24e80202ea134722b3e462798db290da"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["train-00000-of-00001.parquet:   0%|          | 0.00/299M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"062b5dbf71ff412fa5c169376f78bc31"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["test-00000-of-00001.parquet:   0%|          | 0.00/23.5M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f2773bd9eeb943a5b7335d9b144756fb"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Generating train split:   0%|          | 0/650000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"25f9fa2bd7d7482f9958bd385cd36da1"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Generating test split:   0%|          | 0/50000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a1e3cfec50f1486487f184ad9b207f52"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["data type = type(dataset)\n"]}],"source":["from datasets import Dataset, DatasetDict, load_dataset\n","\n","# Load train and test splits separately\n","train_dataset = load_dataset(\"yelp_review_full\", split=\"train[:5000]\")\n","test_dataset = load_dataset(\"yelp_review_full\", split=\"test[:1000]\")\n","# Create a DatasetDict\n","dataset = DatasetDict({\n","    \"train\": train_dataset,\n","    \"test\": test_dataset,\n","})\n","\n","print(f\"data type = type(dataset)\")"]},{"cell_type":"code","source":["# Dataset structure\n","dataset"],"metadata":{"id":"lh-sYZrcEV4E","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741180691029,"user_tz":-480,"elapsed":5,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"f1c1bad4-1630-4af9-b3dc-b32d7f23701f"},"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DatasetDict({\n","    train: Dataset({\n","        features: ['label', 'text'],\n","        num_rows: 5000\n","    })\n","    test: Dataset({\n","        features: ['label', 'text'],\n","        num_rows: 1000\n","    })\n","})"]},"metadata":{},"execution_count":4}]},{"cell_type":"markdown","source":["#Step 2: Create the model and tokenizer objects"],"metadata":{"id":"cDY9W23f7YXi"}},{"cell_type":"code","execution_count":5,"metadata":{"id":"2iUVb1RF9fp7","colab":{"base_uri":"https://localhost:8080/","height":281,"referenced_widgets":["b26c37aa3e05446e800b688ee83c32b6","8332e9c7029c44b0a47b03ab10c79ad1","3ea83a5167824c26abc8ea1ad159f3b5","8718484de6c94a70a3796a0cf2690332","ed3b976173bc48d888a9cfd6f66c29f9","6ff29a7ba26248e7a38232ef88ac9685","e325048f714e4a0383b074db5602a804","0ad7b931450d45079560b1ef8520b16f","c0606d6c0419418ba0bde9d5d1f13e23","d651d5bb14dc43d49de9e7f1e37739e5","9c00c75d620d4b02866471f2f6348765","44b43d19805c4983980946c6a0472822","62e43ba25be4463f94842d34f2f0576c","eb46e130a99f45d582e1a028e0a93345","15e0ab0d275d47ca82af3a9873aaea02","3a9759fbd69a4ecb97ae39abefd955b0","9bf766da20254b65807a7d8cf58a9b21","b6d12b58372a43ca8b692758aa1352bb","ea481211d3d74bbc836a7bb7efcbe42b","5573353d72c14acd886b068cec3e3177","d046fec1f48f4723acff182bc68796d8","b01a07ab844242659d5ba2b88da36532","4562299ad45a400483c55320a327947c","2f5cb473638b4488a0a97b22fd7f13a1","26c82aa5d81e4317b871e32ea619ad7e","d27aaf745508497e94db2191651860f1","5db12d99747045a1a138b72592e68b50","804226bb3a9c4663bd49da6d2acf1234","67a21f4386854e189c03c45cecea8307","8948b6fcdac94bfba3e883e4585b521e","85b0386444334f769c5026c0893e5469","85fc96557cb94fa3b482dba54209cbaf","99c1516a6b944284bdeef5bff4feb790","6c2538c16f2d4397a41eeaeacc68edd8","554b497c1c6f4dc2afeec74027d506f8","40d6ea3d61a4491a8945d4c890c36bd2","b22c011b05ec45849b9d0a39c6034726","7b11aa829ded4eac95ae5599ed9b4c4d","c17d17553a0f465bba3ece8946bbd7f5","99431d3df6284012b024fb76b7da7220","738fa1585b9c4c4a9f8e42a26904e3f6","5b85a8ac9f3747f19b846ba118a0bf91","3a86a403461b4726b66ff05b5ad1d9c0","ba6e2f04e2754c849139093865cc9751","f905498f89894a63a94cd6693bc1bb6f","00141abcdfa54f70a4f0cd8fc85ba5c4","3c20e265fc80476ba1dd51b40393b2e9","5064de103fbb4604aee9d2009de862b4","60b76a771af848c6a67e329246d33444","ae13c14b0ba44cf0adb4ebe331a95d85","1acb271631cd48b3bc634aeedfc71261","d3694e48522340bd8aaa4c88153a0f29","38a7272157444a4eb664ad40bc811d8a","753838f22167458084a54bb9d6dc666d","d929a2dffcb14fb08000314fde83933b","8e9166a39ec24b2fa485428e9924ce47","e25410d043dc454582fa26cd008b9aff","52de21e8c5e0478b82479074890e3255","cdeaaf4997564d99954b7e0dde23d20a","8cfa63dd60e6430199efaa7ae5e8b17b","1f9ae98619224d57b9c3f005214f539b","e471215c1fd64f279efbbd12ac09b5cc","c1cb8920b36344838913c5f47ad63900","4a1f5d18ec814f5bb8bbc50b7240fe82","b6e0b26661474662985556063e7c9e2d","36784f06dfa743bda090a1d87ec951b9"]},"executionInfo":{"status":"ok","timestamp":1741180726494,"user_tz":-480,"elapsed":35464,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"d80e620a-9d8c-4cf7-8e33-3e9d5db14c69"},"outputs":[{"output_type":"stream","name":"stderr","text":["The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"]},{"output_type":"display_data","data":{"text/plain":["0it [00:00, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b26c37aa3e05446e800b688ee83c32b6"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["config.json:   0%|          | 0.00/483 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"44b43d19805c4983980946c6a0472822"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4562299ad45a400483c55320a327947c"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Some weights of DistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight', 'pre_classifier.bias', 'pre_classifier.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"]},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6c2538c16f2d4397a41eeaeacc68edd8"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f905498f89894a63a94cd6693bc1bb6f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer.json:   0%|          | 0.00/466k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8e9166a39ec24b2fa485428e9924ce47"}},"metadata":{}}],"source":["from transformers import AutoModelForSequenceClassification\n","from transformers import AutoTokenizer\n","\n","model = AutoModelForSequenceClassification.from_pretrained(\"distilbert-base-uncased\",\n","                                                           num_labels=5)\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert-base-uncased\")"]},{"cell_type":"markdown","source":["#Step 3: Generate Dataset for Funetuning"],"metadata":{"id":"jl-YsumaCk3P"}},{"cell_type":"code","source":["type(dataset)"],"metadata":{"id":"Tbzor03hH41D","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741180726503,"user_tz":-480,"elapsed":10,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"45c56085-c54b-4562-b408-e3acd583cb3b"},"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["datasets.dataset_dict.DatasetDict"]},"metadata":{},"execution_count":6}]},{"cell_type":"code","execution_count":7,"metadata":{"id":"P_gNo-IM9fp6","colab":{"base_uri":"https://localhost:8080/","height":81,"referenced_widgets":["8ede96f846864474819ccf3fd5b29add","ff1b213e3b16431aad4a91af3cb267f4","7fb70a7941ce41d59560736bf091aea3","a253873632c046dc8c76c1c3c8505fbf","179ea1f11e634985a1e41300940e2d62","70c2cdca9f3743ca807f718ee7ba7095","bc2a43e8a24c442faec8d28ed8cba49c","fd9f80d0d197460c81c47d2523214e31","43ec733e5db34e16bb75fd1492699335","1d9ff3b71d7f427caa49f634acf48d9b","ad99a3f7e8c749f6924ada7bb03095c4","378928707dd247b29bbd2340a1666d24","b10c5bcaf3d547c0a52d09c862b5df5a","b9af3257d6d74fb993b71d421dd431ba","d89b3a24bb3a43ee8de56e380e6d5eb3","8fdd930004584238bf7fee9ec0580ead","f363bd98cd5344a998a6c2c6a3b69577","0bf9a4a2b8c241698bbb834f6f615e87","cb4fe5328e0e4243bc8bd03958e595df","9c55a89667454dccb972640df19dd518","5f3acd5c476743bb8d7103a8bee59694","b8d64925da3540cd841ba1b9dcdf5fba"]},"executionInfo":{"status":"ok","timestamp":1741180730497,"user_tz":-480,"elapsed":3993,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"1f7e62b4-3ccc-468a-f08a-882d339a3d48"},"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/5000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8ede96f846864474819ccf3fd5b29add"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/1000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"378928707dd247b29bbd2340a1666d24"}},"metadata":{}}],"source":["from transformers import AutoTokenizer\n","\n","def tokenize_function(examples):\n","    return tokenizer(examples[\"text\"], padding=\"max_length\", truncation=True)\n","\n","tokenized_datasets = dataset.map(tokenize_function, batched=True)\n","\n","small_train_dataset = tokenized_datasets[\"train\"].shuffle(seed=42).select(range(1000))\n","small_eval_dataset = tokenized_datasets[\"test\"].shuffle(seed=42).select(range(1000))"]},{"cell_type":"markdown","source":["#Step 4a: Finetune the pre-trained model"],"metadata":{"id":"juxfjn75O5x5"}},{"cell_type":"code","execution_count":8,"metadata":{"id":"BcykpOK6jK6R","colab":{"base_uri":"https://localhost:8080/","height":173,"referenced_widgets":["e02e8f81ea9b4110a1b7243691e79f8e","d992b675cda14b70a70e5b64cdab60fe","8ba76c8d43b44a0b82ba53601b014bff","ac7d3cd00e5f490cb56a042502806159","a008c0533d9e47cca97244f79e92b842","242eba04d2ec4d8eb01b39bca536b711","15fb26c016764951a98c0090f3c87e74","d503b5c625084f8cb2d8cefc1479fbd8","556b6553417b478d952da8b68eb6b8c4","4db22d32f5604b79acb550c8e00edfb9","b74297a3c4204505b7fffbc3ae87245e"]},"executionInfo":{"status":"ok","timestamp":1741180800572,"user_tz":-480,"elapsed":70076,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"a582bff1-32a5-4251-9424-f20dc7a6415b"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='125' max='125' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [125/125 01:05, Epoch 1/1]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Epoch</th>\n","      <th>Training Loss</th>\n","      <th>Validation Loss</th>\n","      <th>Accuracy</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>1</td>\n","      <td>No log</td>\n","      <td>1.211276</td>\n","      <td>0.472000</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading builder script:   0%|          | 0.00/4.20k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e02e8f81ea9b4110a1b7243691e79f8e"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["TrainOutput(global_step=125, training_loss=1.425005615234375, metrics={'train_runtime': 67.4647, 'train_samples_per_second': 14.823, 'train_steps_per_second': 1.853, 'total_flos': 132474485760000.0, 'train_loss': 1.425005615234375, 'epoch': 1.0})"]},"metadata":{},"execution_count":8}],"source":["from transformers import TrainingArguments\n","from evaluate import load\n","from transformers import TrainingArguments, Trainer\n","import numpy as np\n","\n","def compute_metrics(eval_pred):\n","    logits, labels = eval_pred\n","    predictions = np.argmax(logits, axis=-1)\n","    metric = load(\"accuracy\")\n","    return metric.compute(predictions=predictions, references=labels)\n","\n","\n","# metric = load_metric(\"accuracy\")\n","training_args = TrainingArguments(output_dir=\"test_trainer\",\n","                                  num_train_epochs=1,\n","                                  eval_strategy=\"epoch\")\n","trainer = Trainer(\n","    model=model,\n","    args=training_args,\n","    train_dataset=small_train_dataset,\n","    eval_dataset=small_eval_dataset,\n","    compute_metrics=compute_metrics,\n",")\n","\n","trainer.train()"]},{"cell_type":"markdown","source":["#Step 4b: Evaluate the finetuned model\n","\n","\n"],"metadata":{"id":"NS0ttJRbIEDU"}},{"cell_type":"code","source":["trainer.evaluate()"],"metadata":{"id":"xO_5738u4lwa","colab":{"base_uri":"https://localhost:8080/","height":141},"executionInfo":{"status":"ok","timestamp":1741180817022,"user_tz":-480,"elapsed":16452,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"35bf249d-96ff-4a2b-cae1-ba8c530ccd65"},"execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='125' max='125' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [125/125 00:15]\n","    </div>\n","    "]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["{'eval_loss': 1.211275577545166,\n"," 'eval_accuracy': 0.472,\n"," 'eval_runtime': 16.4539,\n"," 'eval_samples_per_second': 60.776,\n"," 'eval_steps_per_second': 7.597,\n"," 'epoch': 1.0}"]},"metadata":{},"execution_count":9}]},{"cell_type":"markdown","source":["#Step 4c: Save the finetuned model"],"metadata":{"id":"vv9uQiGsbs5G"}},{"cell_type":"code","source":["trainer.save_model('CustomModel_yelp')"],"metadata":{"id":"5h4u7yyp4mhB","executionInfo":{"status":"ok","timestamp":1741180818133,"user_tz":-480,"elapsed":1106,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}}},"execution_count":10,"outputs":[]},{"cell_type":"code","source":["!zip -r /content/CustomModel_yelp.zip CustomModel_yelp"],"metadata":{"id":"22qSxJez4mPs","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741180833037,"user_tz":-480,"elapsed":14897,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"1f14efb1-05dc-4eaf-fd14-9a4070cf786e"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["  adding: CustomModel_yelp/ (stored 0%)\n","  adding: CustomModel_yelp/training_args.bin (deflated 52%)\n","  adding: CustomModel_yelp/model.safetensors (deflated 8%)\n","  adding: CustomModel_yelp/config.json (deflated 51%)\n"]}]},{"cell_type":"code","source":["from google.colab import files\n","files.download(\"CustomModel_yelp.zip\")"],"metadata":{"id":"RpxIaGSJ4pPD","colab":{"base_uri":"https://localhost:8080/","height":17},"executionInfo":{"status":"ok","timestamp":1741180833040,"user_tz":-480,"elapsed":20,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"89a3c97d-a850-466a-e6dd-8ec0018155cf"},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.Javascript object>"],"application/javascript":["\n","    async function download(id, filename, size) {\n","      if (!google.colab.kernel.accessAllowed) {\n","        return;\n","      }\n","      const div = document.createElement('div');\n","      const label = document.createElement('label');\n","      label.textContent = `Downloading \"${filename}\": `;\n","      div.appendChild(label);\n","      const progress = document.createElement('progress');\n","      progress.max = size;\n","      div.appendChild(progress);\n","      document.body.appendChild(div);\n","\n","      const buffers = [];\n","      let downloaded = 0;\n","\n","      const channel = await google.colab.kernel.comms.open(id);\n","      // Send a message to notify the kernel that we're ready.\n","      channel.send({})\n","\n","      for await (const message of channel.messages) {\n","        // Send a message to notify the kernel that we're ready.\n","        channel.send({})\n","        if (message.buffers) {\n","          for (const buffer of message.buffers) {\n","            buffers.push(buffer);\n","            downloaded += buffer.byteLength;\n","            progress.value = downloaded;\n","          }\n","        }\n","      }\n","      const blob = new Blob(buffers, {type: 'application/binary'});\n","      const a = document.createElement('a');\n","      a.href = window.URL.createObjectURL(blob);\n","      a.download = filename;\n","      div.appendChild(a);\n","      a.click();\n","      div.remove();\n","    }\n","  "]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.Javascript object>"],"application/javascript":["download(\"download_4edabfdd-f512-4b45-8822-a4ad774d7dbb\", \"CustomModel_yelp.zip\", 246790064)"]},"metadata":{}}]},{"cell_type":"markdown","source":["#Step 5: Test the saved model"],"metadata":{"id":"N35Jqc8OSCvU"}},{"cell_type":"code","source":["# Testing with the saved model\n","# model = AutoModelForSequenceClassification.from_pretrained(\"distilbert-base-uncased\",\n","                                                          #  num_labels=5)\n","model2 = AutoModelForSequenceClassification.from_pretrained(\"CustomModel_yelp\",\n","                                                           num_labels=5)\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert-base-uncased\")"],"metadata":{"id":"cp47bXVtR5Sp","executionInfo":{"status":"ok","timestamp":1741180833285,"user_tz":-480,"elapsed":255,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}}},"execution_count":13,"outputs":[]},{"cell_type":"code","source":["#Tokenized testing data\n","\n","# tokenizer = AutoTokenizer.from_pretrained(\"distilbert-base-uncased\")\n","# label: 0\n","text = \"My expectations for McDonalds are t rarely high. But for one to still fail so spectacularly...that takes something special!\\\\nThe cashier took my friends\\'s order, then promptly ignored me. I had to force myself in front of a cashier who opened his register to wait on the person BEHIND me. I waited over five minutes for a gigantic order that included precisely one kid\\'s meal. After watching two people who ordered after me be handed their food, I asked where mine was. The manager started yelling\"\n","inputs = tokenizer(text,\n","                   padding = True,\n","                   truncation = True,\n","                   return_tensors='pt')"],"metadata":{"id":"UO-FcOF3wSD_","executionInfo":{"status":"ok","timestamp":1741180833290,"user_tz":-480,"elapsed":3,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}}},"execution_count":14,"outputs":[]},{"cell_type":"code","source":["import torch\n","import numpy as np\n","\n","outputs = model2(**inputs)\n","\n","predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)\n","predictions = predictions.cpu().detach().numpy()\n","print(f\"The predicted class is {np.argmax(predictions)}\")\n","print(f\"Class 0={predictions[0,0]:.4f}, Class 1={predictions[0,1]:.4f}\")\n","print(f\"Class 2={predictions[0,2]:.4f}, Class 3={predictions[0,3]:.4f}\")\n","print(f\"Class 4={predictions[0,4]:.4f}\")"],"metadata":{"id":"ezfASAJTsfSn","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741181174160,"user_tz":-480,"elapsed":460,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"131b2711-e657-475c-ceee-226903fae6a1"},"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["The predicted class is 0\n","Class 0=0.5495, Class 1=0.2073\n","Class 2=0.1306, Class 3=0.0561\n","Class 4=0.0565\n"]}]},{"cell_type":"markdown","source":["# Testing with the Saved Model (Full Program)"],"metadata":{"id":"jUEIecT_S3ez"}},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"id":"DgyYXBIn7Grm","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741105737277,"user_tz":-480,"elapsed":27939,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"a0a400a4-34d1-4f0f-cc9f-8e4fe4c8195b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["!unzip <<file location>> -d ."],"metadata":{"id":"ES3QhKLZ6SVr"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["from transformers import AutoModelForSequenceClassification\n","from transformers import AutoTokenizer\n","import torch\n","import numpy as np\n","\n","# Testing with the saved model\n","model2 = AutoModelForSequenceClassification.from_pretrained(\"CustomModel_yelp\",\n","                                                            num_labels=5)\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert-base-uncased\")\n","\n","# Tokenized testing data\n","label = 4 # label = 4\n","text = \"dr. goldberg offers everything i look for in a general practitioner. he's nice and easy to talk to without being patronizing; he's always on time in seeing his patients; he's affiliated with a top-notch hospital (nyu) which my parents have explained to me is very important in case something happens and you need surgery; and you can get referrals to see specialists without having to see him first. really, what more do you need? i'm sitting here trying to think of any complaints i have about him, but i'm really drawing a blank.\"\n","inputs = tokenizer(text,\n","                   padding=True,\n","                   truncation=True,\n","                   return_tensors='pt')\n","\n","outputs = model2(**inputs)\n","predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)\n","predictions = predictions.cpu().detach().numpy()\n","\n","# Get the index of the largest output value\n","max_index = np.argmax(predictions)\n","\n","print(f\"The label is {label} and the predicted label is {max_index}\")"],"metadata":{"id":"-JIan8Ambh9h","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1741181191332,"user_tz":-480,"elapsed":484,"user":{"displayName":"ISOM5240 Instructor","userId":"00019301581892291369"}},"outputId":"ffdd722c-3a1f-490d-c1b4-977f266a9bdc"},"execution_count":16,"outputs":[{"output_type":"stream","name":"stdout","text":["The label is 4 and the predicted label is 4\n"]}]}]}
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