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Flipkart Customer Reviews\n","\n","Dataset Source: [Kaggle](https://www.kaggle.com/datasets/niraliivaghani/flipkart-product-customer-reviews-dataset)\n","\n","## <b>Sentiment Analysis</b>\n","\n","### <b><i>Using DistilBERT model to fine-tune it on the data</i></b>\n","\n","<br><br><br>\n","### Results:\n","\n","Sentiment Categories - <i>Positive, Negative, Neutral</i> \n","\n","Recall: 0.94\n","Precision: 0.94\n","\n","\n","<br><br><br>"],"metadata":{"id":"jNu_KPYsjwx5"}},{"cell_type":"markdown","source":["## Libraries and Data"],"metadata":{"id":"lkzd1Kqck-Sy"}},{"cell_type":"code","source":["# import locale\n","# locale.getpreferredencoding = lambda: \"UTF-8\"\n","!pip install datasets transformers\n"],"metadata":{"id":"O5u0s2NrmILv"},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":3,"metadata":{"id":"HxALm0Tt1Hsw","executionInfo":{"status":"ok","timestamp":1679959781276,"user_tz":-60,"elapsed":1087,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import spacy\n","from spacy import displacy\n","from datasets import load_dataset, Dataset\n","\n","import torch\n","from transformers import AutoTokenizer, DataCollatorWithPadding, AutoModelForSequenceClassification, TrainingArguments, Trainer\n","from datasets import load_metric\n"]},{"cell_type":"code","source":["# Read data \n","\n","data = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/Flipkart Product Reviews - Kaggle/Dataset-SA.csv')\n","\n","# Convert sentiments to category and drop NA value rows\n","\n","data['sentiment_code'] = pd.Categorical(data.Sentiment).codes\n","data['sentiment_code'] = data['sentiment_code'].astype('Int64')\n","data.dropna(inplace = True)\n","\n","# Convert data into Dataset object for using with distilBERT\n","\n","data_2 = Dataset.from_pandas(data[['Summary', 'sentiment_code']])\n"],"metadata":{"id":"0KjYr-gt1NBx","executionInfo":{"status":"ok","timestamp":1679959789986,"user_tz":-60,"elapsed":3068,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":4,"outputs":[]},{"cell_type":"code","source":["data.head()"],"metadata":{"id":"Q-LTJEie1N7-","executionInfo":{"status":"ok","timestamp":1679959796457,"user_tz":-60,"elapsed":254,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":206},"outputId":"eba5f41a-639f-40b0-e23b-70dac9eea199"},"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                        product_name product_price Rate  \\\n","0  Candes 12 L Room/Personal Air Cooler??????(Whi...          3999    5   \n","1  Candes 12 L Room/Personal Air Cooler??????(Whi...          3999    5   \n","2  Candes 12 L Room/Personal Air Cooler??????(Whi...          3999    3   \n","3  Candes 12 L Room/Personal Air Cooler??????(Whi...          3999    1   \n","4  Candes 12 L Room/Personal Air Cooler??????(Whi...          3999    3   \n","\n","            Review                                            Summary  \\\n","0           super!  great cooler excellent air flow and for this p...   \n","1          awesome              best budget 2 fit cooler nice cooling   \n","2             fair  the quality is good but the power of air is de...   \n","3  useless product                  very bad product its a only a fan   \n","4             fair                                      ok ok product   \n","\n","  Sentiment  sentiment_code  \n","0  positive               2  \n","1  positive               2  \n","2  positive               2  \n","3  negative               0  \n","4   neutral               1  "],"text/html":["\n","  <div id=\"df-58260bea-1dde-464e-8a96-156cbc680b86\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style 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Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"d808b0e2-8c8a-4ca8-d19b-f10b9f630065"},"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["180379"]},"metadata":{},"execution_count":6}]},{"cell_type":"code","source":["data.Sentiment.value_counts()"],"metadata":{"id":"SuLEIfnd1N2B","executionInfo":{"status":"ok","timestamp":1679959801024,"user_tz":-60,"elapsed":197,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"5a527460-4ea0-4608-f1a7-46b3702baa28"},"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["positive    147171\n","negative     24401\n","neutral       8807\n","Name: Sentiment, dtype: int64"]},"metadata":{},"execution_count":7}]},{"cell_type":"code","source":["data.Summary[0]"],"metadata":{"id":"hcRptwsW1NzL","executionInfo":{"status":"ok","timestamp":1679959802561,"user_tz":-60,"elapsed":238,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"aff9853e-5b6b-47b7-c02f-ba20c53021bd"},"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'great cooler excellent air flow and for this price its so amazing and unbelievablejust love it'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":8}]},{"cell_type":"code","source":[],"metadata":{"id":"TQhsoEN_1Nwf"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Modelling"],"metadata":{"id":"fPEKehFelF5z"}},{"cell_type":"code","source":["torch.cuda.is_available()"],"metadata":{"id":"gDOGEs-uf2dz","executionInfo":{"status":"ok","timestamp":1679959805709,"user_tz":-60,"elapsed":275,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"55f979d3-65ec-4746-b699-87b1eb23f956"},"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{},"execution_count":9}]},{"cell_type":"code","source":["# Train-Test data split\n","\n","train = data_2.shuffle(seed=42).select([i for i in list(range(20000))])\n","test = data_2.shuffle(seed=42).select([i for i in list(range(20000, len(data_2)))])\n","\n","\n","print(train[0])\n","print(test[0])"],"metadata":{"id":"FQB9GwLZf2a-","executionInfo":{"status":"ok","timestamp":1679959809493,"user_tz":-60,"elapsed":848,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"33b73b90-8c56-4c80-b60e-b9f06372c849"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["{'Summary': 'good quality product i think price little bit high otherwise awesome stuff', 'sentiment_code': 2, '__index_level_0__': 138001}\n","{'Summary': 'gud product', 'sentiment_code': 2, '__index_level_0__': 17880}\n"]}]},{"cell_type":"code","source":["# Load tokenizer from distilBERT\n","\n","tokenizer = AutoTokenizer.from_pretrained(\"distilbert-base-uncased\")"],"metadata":{"id":"6yTuEtK4f2TB","executionInfo":{"status":"ok","timestamp":1679959812982,"user_tz":-60,"elapsed":1487,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["c3954412286b452b8bf3ee39ede6993a","89bc68e8ff974f40bccb5f142d8a211c","d74a006c770d455a9c49446c52114021","26c0e02dabdf4a228b89af41b23ec7ce","bdbd1c3dfd0f42868de11d5c0171cf4b","682f8bdc00084ba581baff1caa314969","48df033cebad4eaca7d1003d64c48c6a","f7cadaac0df04b28a16f43262a9d7b9d","92349ad29b064814bde5d6a12f4962a1","43a2a8a05f8e4da5b14b3dae3988e930","5745cf36c17b4a1e81bcf05818745af8","e0bbfdfb0d0845f3882e9a8d83ef6919","2a49bb36b34c4c27ab2bfbec26edd0ce","0693767694fe4660a4ac2a09bb0e1e19","0509db0ce4e04b449c44de93bd9bdd53","fffc86979a6049ae945a62058e60973b","563676a38758467eabf2fa95b9d6f83d","07f1aa0b97f64ae3be27221d28b7b3ad","90f8dda3300f4bd1a2b37fc3fc3d41a4","f0e87567566143649c9963dfec664686","c13c1fdc322a4c82bc7807248e30f49b","0a58f2cebacd45e0aa142cd8c6223fe7","91e9c0e75c374ec681d21a9d0755ed99","a1c29a5ef592482eb4324a7f82b4ded8","fa916899cca44751a708510b4fdbb638","6adcbb046e36497ca5c323f361ad80c5","f84ed2fe037d4250b919d1e13d4da0e5","6519daf6fc5644daa55c7042a91d0c24","5fcaa2112ddc474eb040d88871f69c90","200f7a69631742008d3d77e10028a314","286b3b30dd274f2f8f153f3328d97302","372c12c6071b46bba3fc280e754fbdd7","4ce3ee8519f64291bffba38d9ae30da3","13841d56076c4bebab619fb863f0960c","6e8fbe8e2ac14814b3be62d307f45233","a1dcd86dfea34cedb224d741d65bcc71","170d7bd055ec4b64be7fc129135db7aa","ee31bf7f6a0847ebb20e9be5c2398ffe","7c2e41e388a04914bacf54bb93026a78","aacc896081bb4468bc45f371acbaa6f4","2e8714c7e47f4c1996c908b7076624dc","deee81699362478199c2dbf1b25951d2","8402e93b16bf4d5a8815f834eab769f8","250a3d940c6a408cb43de7430d8a5569"]},"outputId":"500c32ac-b352-481e-e29e-66f1507ceb5c"},"execution_count":11,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c3954412286b452b8bf3ee39ede6993a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/483 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e0bbfdfb0d0845f3882e9a8d83ef6919"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)solve/main/vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"91e9c0e75c374ec681d21a9d0755ed99"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)/main/tokenizer.json:   0%|          | 0.00/466k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"13841d56076c4bebab619fb863f0960c"}},"metadata":{}}]},{"cell_type":"code","source":["# Tokenize train and test data\n","\n","def tokenize_function(df):\n","    return tokenizer(df[\"Summary\"], truncation=True)\n","\n","tokenized_train = train.map(tokenize_function, batched=True)\n","tokenized_test = test.map(tokenize_function, batched=True)"],"metadata":{"id":"VqhWzhwhiJol","executionInfo":{"status":"ok","timestamp":1679959829221,"user_tz":-60,"elapsed":13436,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":17,"referenced_widgets":["4201b656660a4a59aefdb04d1e30bb04","b59d50b0d5de4c3b865c9f82b3f4dc11","0a367642cf6648ebb71afffdbb797def","33f13d8d25f84e4784b38db7d4ae14fa","1de5ead92ce44cc3abe84128060be8da","a93d7d77d3ed42dc988fd064113c9a0a","a55e6ef1dabb4e1e83b6783ae929726f","8a6badc69e864978bafdb50743dd6ced","0cb115e96eec4885bc41e6b810efe538","1112540d6cb1438899b41f4b89df0867","c2664778a81244279e6a8e950c74db11","6cfefab2f54a4329808943bb6d353b3b","15248ecbf3d84058860f3f64d1e81315","5d6b36aa50ba4f4da92516e7be5a87c1","d52960a7ee564343be28bf534afdf37f","43469007d3bd402f854a94be1ce1f19c","62f3a7cfee4347d898700037ca6b9b92","65e3f0bf0fd44dffafe845b094529717","923687016b9a4badaebb64211fc9b6a1","c83047a3f7e2485cbb8b87616d469a98","0aa826e2c04f49c1ac6de73b90cea664","81ac4e129b9a4a889e66fb9e81796b8d"]},"outputId":"8c5f2d8c-e116-4604-a573-b99b5b1a726d"},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":["Map: 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tokenized_test.rename_column(\"sentiment_code\", \"labels\")\n"],"metadata":{"id":"sVCUxkG3iJik","executionInfo":{"status":"ok","timestamp":1679959834245,"user_tz":-60,"elapsed":198,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":13,"outputs":[]},{"cell_type":"code","source":["tokenized_test"],"metadata":{"id":"iEVMozo4kh2g","executionInfo":{"status":"ok","timestamp":1679959838179,"user_tz":-60,"elapsed":202,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"66f4ba6f-8554-40ed-fe07-821d791b1f81"},"execution_count":14,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Dataset({\n","    features: ['text', 'labels', 'input_ids', 'attention_mask'],\n","    num_rows: 160379\n","})"]},"metadata":{},"execution_count":14}]},{"cell_type":"code","source":["# Define data collator\n","\n","data_collator = DataCollatorWithPadding(tokenizer=tokenizer)\n","\n","# Define DistilBERT\n","model = AutoModelForSequenceClassification.from_pretrained(\"distilbert-base-uncased\", num_labels=3)"],"metadata":{"id":"gAOYpd4diJfr","executionInfo":{"status":"ok","timestamp":1679959845897,"user_tz":-60,"elapsed":5074,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":160,"referenced_widgets":["944a080b8a6d46f5ae597fe8348e42b2","0084cd1a9b14447695f86f9571909364","6247bf6883f84358b22552105d7ecd64","ca310417416d48be9351decee8f964db","bf605efcfb194c67aefe319545fa9ef0","f4667cf636834bd8a3bb0d95fc84500d","5a9dde41d9ac4ba8b21c78aa5e990e28","c044a6154cd9478bb12150b446027bce","2c36f60bb9d349509ce0aadd2d8a97a3","b925047be9814a259f4691dbf0e76c35","d8838694a2cc428897a4a5db81de4c6c"]},"outputId":"b4f64678-98a2-4431-bf05-3262cea36623"},"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading pytorch_model.bin:   0%|          | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"944a080b8a6d46f5ae597fe8348e42b2"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Some weights of the model checkpoint at distilbert-base-uncased were not used when initializing DistilBertForSequenceClassification: ['vocab_projector.bias', 'vocab_layer_norm.weight', 'vocab_layer_norm.bias', 'vocab_transform.bias', 'vocab_projector.weight', 'vocab_transform.weight']\n","- This IS expected if you are initializing DistilBertForSequenceClassification 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","- This IS NOT expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n","Some weights of DistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['pre_classifier.weight', 'classifier.weight', 'pre_classifier.bias', 'classifier.bias']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"]}]},{"cell_type":"code","source":["# Define function to compute metrics\n","\n","def compute_metrics(eval_pred):\n","\n","    load_recall = load_metric('recall')\n","    load_precision = load_metric('precision')\n","    \n","    logits, labels = eval_pred\n","    predictions = np.argmax(logits, axis=-1)\n","    \n","    recall = load_recall.compute(predictions = predictions, references=labels, average=\"micro\")[\"recall\"]\n","    precision = load_precision.compute(predictions = predictions, references=labels, average=\"micro\")[\"precision\"]\n","\n","    return {\"recall\": recall, \"precision\": precision}"],"metadata":{"id":"2gCzaWJeiJVt","executionInfo":{"status":"ok","timestamp":1679963313322,"user_tz":-60,"elapsed":214,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":20,"outputs":[]},{"cell_type":"code","source":["# Define trainer object for model training and evaluation\n","\n","repo_name = '/content/drive/MyDrive/Colab Notebooks/Flipkart Product Reviews - Kaggle'\n","\n","\n","training_args = TrainingArguments(\n","    output_dir=repo_name,\n","    learning_rate=2e-5,\n","    per_device_train_batch_size=16,\n","    per_device_eval_batch_size=16,\n","    num_train_epochs=10,\n","    weight_decay=0.01,\n","    save_strategy=\"epoch\"\n",")\n","\n","trainer = Trainer(\n","    model=model,\n","    args=training_args,\n","    train_dataset=tokenized_train,\n","    eval_dataset=tokenized_test,\n","    tokenizer=tokenizer,\n","    data_collator=data_collator,\n","    compute_metrics=compute_metrics,\n",")"],"metadata":{"id":"I_ZKiDNkiJQD","executionInfo":{"status":"ok","timestamp":1679963324051,"user_tz":-60,"elapsed":257,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":21,"outputs":[]},{"cell_type":"code","source":["# Train model \n","\n","trainer.train()"],"metadata":{"id":"anx-nRQGjjUP","executionInfo":{"status":"ok","timestamp":1679964616497,"user_tz":-60,"elapsed":1231051,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":952},"outputId":"2a916cdf-540c-47ce-f65f-88e403c1a37f"},"execution_count":22,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.9/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","  warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='12500' max='12500' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [12500/12500 20:30, Epoch 10/10]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>500</td>\n","      <td>0.029600</td>\n","    </tr>\n","    <tr>\n","      <td>1000</td>\n","      <td>0.029300</td>\n","    </tr>\n","    <tr>\n","      <td>1500</td>\n","      <td>0.023800</td>\n","    </tr>\n","    <tr>\n","      <td>2000</td>\n","      <td>0.029600</td>\n","    </tr>\n","    <tr>\n","      <td>2500</td>\n","      <td>0.035500</td>\n","    </tr>\n","    <tr>\n","      <td>3000</td>\n","      <td>0.027500</td>\n","    </tr>\n","    <tr>\n","      <td>3500</td>\n","      <td>0.027900</td>\n","    </tr>\n","    <tr>\n","      <td>4000</td>\n","      <td>0.020800</td>\n","    </tr>\n","    <tr>\n","      <td>4500</td>\n","      <td>0.022800</td>\n","    </tr>\n","    <tr>\n","      <td>5000</td>\n","      <td>0.026800</td>\n","    </tr>\n","    <tr>\n","      <td>5500</td>\n","      <td>0.019100</td>\n","    </tr>\n","    <tr>\n","      <td>6000</td>\n","      <td>0.021600</td>\n","    </tr>\n","    <tr>\n","      <td>6500</td>\n","      <td>0.020300</td>\n","    </tr>\n","    <tr>\n","      <td>7000</td>\n","      <td>0.024200</td>\n","    </tr>\n","    <tr>\n","      <td>7500</td>\n","      <td>0.022800</td>\n","    </tr>\n","    <tr>\n","      <td>8000</td>\n","      <td>0.016300</td>\n","    </tr>\n","    <tr>\n","      <td>8500</td>\n","      <td>0.021300</td>\n","    </tr>\n","    <tr>\n","      <td>9000</td>\n","      <td>0.020400</td>\n","    </tr>\n","    <tr>\n","      <td>9500</td>\n","      <td>0.016000</td>\n","    </tr>\n","    <tr>\n","      <td>10000</td>\n","      <td>0.022000</td>\n","    </tr>\n","    <tr>\n","      <td>10500</td>\n","      <td>0.017500</td>\n","    </tr>\n","    <tr>\n","      <td>11000</td>\n","      <td>0.018700</td>\n","    </tr>\n","    <tr>\n","      <td>11500</td>\n","      <td>0.015400</td>\n","    </tr>\n","    <tr>\n","      <td>12000</td>\n","      <td>0.020200</td>\n","    </tr>\n","    <tr>\n","      <td>12500</td>\n","      <td>0.015600</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["TrainOutput(global_step=12500, training_loss=0.022602348480224608, metrics={'train_runtime': 1230.6241, 'train_samples_per_second': 162.519, 'train_steps_per_second': 10.157, 'total_flos': 2696856652046880.0, 'train_loss': 0.022602348480224608, 'epoch': 10.0})"]},"metadata":{},"execution_count":22}]},{"cell_type":"code","source":["# Evaluate metrics for model on test data\n","\n","trainer.evaluate()"],"metadata":{"id":"iHmh520sGIOP","executionInfo":{"status":"ok","timestamp":1679964881868,"user_tz":-60,"elapsed":265410,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"colab":{"base_uri":"https://localhost:8080/","height":165},"outputId":"c8bcad6f-3749-4ea2-fdbb-0e09d17a3dbb"},"execution_count":23,"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='10024' max='10024' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [10024/10024 04:22]\n","    </div>\n","    "]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["{'eval_loss': 0.507477343082428,\n"," 'eval_recall': 0.9404660211124898,\n"," 'eval_precision': 0.9404660211124898,\n"," 'eval_runtime': 265.3979,\n"," 'eval_samples_per_second': 604.296,\n"," 'eval_steps_per_second': 37.77,\n"," 'epoch': 10.0}"]},"metadata":{},"execution_count":23}]},{"cell_type":"code","source":[],"metadata":{"id":"Bk5XaQMvsg0U"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":[],"metadata":{"id":"nrP4KIiZsgws"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Saving Model"],"metadata":{"id":"mn9_NmHJlP3H"}},{"cell_type":"code","source":["# Save trained model to directory\n","\n","model_path = '/content/drive/MyDrive/Colab Notebooks/Flipkart Product Reviews - Kaggle/distilbert-base-uncased_finetuned_v2'\n","\n","trainer.save_model(output_dir = model_path)"],"metadata":{"id":"QGxaZRlHiJM8","executionInfo":{"status":"ok","timestamp":1679964883050,"user_tz":-60,"elapsed":1184,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":24,"outputs":[]},{"cell_type":"code","source":["print(\"model saved\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"t_RI1R0pSrs-","executionInfo":{"status":"ok","timestamp":1679964883050,"user_tz":-60,"elapsed":10,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"outputId":"5668683b-bfcc-410e-8544-0adc53e693b1"},"execution_count":25,"outputs":[{"output_type":"stream","name":"stdout","text":["model saved\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"G36ObfqPSwyJ"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Load Model from Memory"],"metadata":{"id":"bLm1QKu-lT2Y"}},{"cell_type":"code","source":["# Load model and tokenizer from memory\n","\n","tokenizer_finetuned = AutoTokenizer.from_pretrained(model_path)\n","model_finetuned = AutoModelForSequenceClassification.from_pretrained(model_path)\n","sentiment_map = {2: \"positive\", \n","                 1: \"neutral\",\n","                 0: \"negative\"}\n"],"metadata":{"id":"YvExJuiff2PR","executionInfo":{"status":"ok","timestamp":1679964884219,"user_tz":-60,"elapsed":1174,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":26,"outputs":[]},{"cell_type":"code","source":["# Define a function to use the model to make predictions\n","\n","def use_model(input_text):\n","\n","  tokenized_text = tokenizer_finetuned(input_text,\n","                                     truncation=True,\n","                                     is_split_into_words=False,\n","                                     return_tensors='pt')\n","  outputs = model_finetuned(tokenized_text[\"input_ids\"])\n","  predicted_label = outputs.logits.argmax(-1)\n","\n","  return(sentiment_map[predicted_label.item()])\n","\n","\n"],"metadata":{"id":"heCR-qIhqcbI","executionInfo":{"status":"ok","timestamp":1679964884220,"user_tz":-60,"elapsed":3,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}}},"execution_count":27,"outputs":[]},{"cell_type":"code","source":["use_model(\"I am not unhappy with this product.\")\n","\n","# Important to note that the model is able to recognize and handle negation in the input statement. "],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":36},"id":"CNt0Fk2yARw6","executionInfo":{"status":"ok","timestamp":1679964884446,"user_tz":-60,"elapsed":229,"user":{"displayName":"Prajwal Premkumar Khairnar","userId":"00356016765080385650"}},"outputId":"c9993d88-b450-41fd-9e9a-3c10446a91be"},"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'positive'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":28}]}]}