{"cells":[{"attachments":{},"cell_type":"markdown","metadata":{},"source":["# FLAN-T5"]},{"attachments":{},"cell_type":"markdown","metadata":{},"source":["## Colab link better looking output:\n","https://colab.research.google.com/drive/1bVujvgH49tyY83eqZoWYcDBZ2JurmLTL?usp=sharing"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"cF27ATTsqUKG"},"outputs":[],"source":["!pip install transformers datasets torch sentencepiece"]},{"cell_type":"code","execution_count":426,"metadata":{"executionInfo":{"elapsed":730,"status":"ok","timestamp":1676231947361,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"8DLGqnFgqcmQ"},"outputs":[],"source":["from datasets import load_dataset\n","from transformers import AutoModelForSeq2SeqLM\n","from transformers import AutoTokenizer\n","import torch\n","from tqdm import tqdm\n","from sklearn.metrics import accuracy_score"]},{"cell_type":"code","execution_count":427,"metadata":{"executionInfo":{"elapsed":2,"status":"ok","timestamp":1676231949164,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"LY2b5R1Wqs7S"},"outputs":[],"source":["def load_and_process_dataset():\n","    dataset = load_dataset(\"sst2\")\n","    dataset.remove_columns('idx')\n","    del dataset['test']\n","    dataset['test'] = dataset['validation']\n","    del dataset['validation']\n","    split_dataset = dataset['train'].train_test_split(test_size=1600)\n","    dataset['train'] = split_dataset['train']\n","    dataset['validation'] = split_dataset['test']\n","    return dataset"]},{"cell_type":"code","execution_count":428,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":329,"referenced_widgets":["a0e441327eee4112ac7b74781c77690e","70fac8ce031c46589955c693c245d627","f44e3cd240a844f9813bc544e68369c6","a9c34e3bd64f4365bf84cca088a67ed3","d3b6970711bd4a91911e36c6b93b0149","b9f228b973bd46c19f87a609f79b376f","80c430dd861144fd84427c50d7afb13c","0882f50062b6429cbcedec4c9538f477","1ba724a4b509400c921c9efc1edb6090","8d90794748b2466b8e9c66c1db803821","f02311e734734bd69180e5e89212f41a"]},"executionInfo":{"elapsed":5033,"status":"ok","timestamp":1676231956945,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"mJK9hcjKqtai","outputId":"6c30f689-268f-43cf-b625-4e10cb12ce0c"},"outputs":[{"name":"stderr","output_type":"stream","text":["WARNING:datasets.builder:Found cached dataset sst2 (/root/.cache/huggingface/datasets/sst2/default/2.0.0/9896208a8d85db057ac50c72282bcb8fe755accc671a57dd8059d4e130961ed5)\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"a0e441327eee4112ac7b74781c77690e","version_major":2,"version_minor":0},"text/plain":["  0%|          | 0/3 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"text/plain":["DatasetDict({\n","    train: Dataset({\n","        features: ['idx', 'sentence', 'label'],\n","        num_rows: 65749\n","    })\n","    test: Dataset({\n","        features: ['idx', 'sentence', 'label'],\n","        num_rows: 872\n","    })\n","    validation: Dataset({\n","        features: ['idx', 'sentence', 'label'],\n","        num_rows: 1600\n","    })\n","})"]},"execution_count":428,"metadata":{},"output_type":"execute_result"}],"source":["dataset = load_and_process_dataset()\n","dataset"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":229,"referenced_widgets":["a0e442f4fa7c4badb0fa1a46840ba751","86fe78ea29bc446a8557cc291ff6300d","502d330613514ca29f1206533282601f","8d568373d5ce4af58f063dc4f30f0b71","465397f6e45a422eaddb86a96af4afd1","449f077725564ebdb8e0096f9aabec99","9f7b2c98a57240c98f1eca099011ae8c","26f887c435a846e39b049cc07ae9f738","bb02703a2688473a8309e9dd4117400a","7a76968e08894d4f886346615873ed8d","8d1a9c60b5334d97be88d9154bef822f","dec176fa12fa4379b0e02e08d0d744f9","339e942966964acba7db87e098e01bb9","186fc01aeb5246f7a3e9da6cc07e1aaf","b53c2d65531f4c5e8a1f0c837856a2e3","64fad61fc73e4fdcb978d8cfcee74b99","c26bd724e80445ccb977ddd9a9139a50","7a0d3d716dc44aeaad3af54cfe4285f3","4ab34af3efdd4f62a8525914852464fd","7feb0c8674264b298a060e9e7b638ee5","33873f8f65414b709d79c575f5d8e89a","3caad1acc3ea432bb563edc5aa4da320","3f06d6aa46ef481ebd785ef89ce955ff","8ffcb9924caa428196d4a8fc749b6c72","17f90dbd86d146ec8c8e1382d89933ee","33e83feb38d84274b8b3c84f2cff5cc9","bb1dbb5ead244ebeb777b15824c7dbdb","50d86ddd37db4bdba4334d5aea132b4a","62ddd18067ed49a081b7e5d36228e169","1e8ab1fa9b7147f7b50ee807a8811ef4","864db41aeccd4a858268d12317ef8d2c","ff7d872e7d5749aa9df9ace32dc42eaf","6e801a6437fa4f488242ec46c14c8d2f","8e5518a8aa0c4a05916e352aa341e56e","2dae19a3df484a979633a1d5b9e70b8f","9ee281173c7a4bb3a94b53709c95860f","b8e9d23f81f84e8ea93e4305e5309d20","f9c9adc55e854f4f866810ada4df1008","bb96fb90bbb2456fac59133e3e86a93f","afdfcc183608406280236a30e8cbf28b","8fa27024d0b8427880ef3aeb563d4aa0","74d97f1d82384b1c99642c9db07d0740","2176b442d1b14878868bb2344db009de","c0e7e0141e254f7bbc5537e085f1b5d1"]},"executionInfo":{"elapsed":9653,"status":"ok","timestamp":1676223155202,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"NJPXwrmJr0eK","outputId":"93a7abdd-d489-4620-9460-48610b515b4b"},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"a0e442f4fa7c4badb0fa1a46840ba751","version_major":2,"version_minor":0},"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/2.54k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"dec176fa12fa4379b0e02e08d0d744f9","version_major":2,"version_minor":0},"text/plain":["Downloading (…)\"spiece.model\";:   0%|          | 0.00/792k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"3f06d6aa46ef481ebd785ef89ce955ff","version_major":2,"version_minor":0},"text/plain":["Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.42M [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"8e5518a8aa0c4a05916e352aa341e56e","version_major":2,"version_minor":0},"text/plain":["Downloading (…)cial_tokens_map.json:   0%|          | 0.00/2.20k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"}],"source":["tokenizer = AutoTokenizer.from_pretrained('google/flan-t5-base')"]},{"cell_type":"code","execution_count":443,"metadata":{"executionInfo":{"elapsed":563,"status":"ok","timestamp":1676232089747,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"Yla8YKK0rYBf"},"outputs":[],"source":["def transform_dataset(dataset):\n","  new_dataset = []\n","\n","  for row in dataset['test']:\n","    text = row['sentence'].replace(\"\\n\", \"\")\n","    new_row = {}\n","    new_row['sentence'] = text\n","    if row['label'] == 0:\n","      new_row['label'] = \"negative\"\n","    else:\n","      new_row['label'] = \"positive\"\n","    new_dataset.append(new_row)\n","  return new_dataset\n","\n","def print_with_index(i):\n","  print(new_dataset[i]['label'],i)\n","\n","def create_predictions(test_data):\n","  predictions = []\n","  expected = []\n","\n","  for row in tqdm(dataset_copy):\n","    input_text = few_shot_example + \" \" + row['sentence'] + \"\\nlabel: \"\n","    input_ids = tokenizer(input_text, return_tensors=\"pt\").input_ids.to(device)\n","\n","    generated_ids = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=200)\n","    generated_text = tokenizer.decode(generated_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)\n","\n","    predictions.append(generated_text)\n","    expected.append(row['label'])\n","  return predictions, expected"]},{"cell_type":"code","execution_count":434,"metadata":{"executionInfo":{"elapsed":2,"status":"ok","timestamp":1676232014907,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"3f8Iy49dKyrk"},"outputs":[],"source":["new_dataset = transform_dataset(dataset)"]},{"cell_type":"code","execution_count":436,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1676232021587,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"yDNbcRUmsGND","outputId":"e32717fa-cf9a-4b86-dc0c-054a3e02f7b9"},"outputs":[{"name":"stdout","output_type":"stream","text":["positive 0\n","negative 46\n","positive 123\n","positive 300\n","positive 400\n","negative 500\n","negative 702\n","negative 802\n","positive 553\n","positive 655\n","positive 455\n","negative 258\n","negative 158\n","negative 752\n","positive 853\n","positive 855\n"]}],"source":["print_with_index(0)\n","print_with_index(46)\n","print_with_index(123)\n","print_with_index(300)\n","print_with_index(400)\n","print_with_index(500)\n","print_with_index(702)\n","print_with_index(802)\n","print_with_index(553)\n","print_with_index(655)\n","print_with_index(455)\n","print_with_index(258)\n","print_with_index(158)\n","print_with_index(752)\n","print_with_index(853)\n","print_with_index(855)\n"]},{"cell_type":"code","execution_count":492,"metadata":{"executionInfo":{"elapsed":1579,"status":"ok","timestamp":1676233275719,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"AEWEe6R24PY9"},"outputs":[],"source":["indexes = [0,553,655,455,258]"]},{"cell_type":"code","execution_count":469,"metadata":{"executionInfo":{"elapsed":3,"status":"ok","timestamp":1676232751201,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"86Z2NQJRNTUR"},"outputs":[],"source":["def create_dataset(indexes):\n","  few_shot_learning_examples = ''\n","  for i in indexes:\n","    few_shot_learning_examples = few_shot_learning_examples + \"sentence: \" + dataset_copy[i]['sentence'] + \"\\n\" +'label: ' + dataset_copy[i]['label'] + '\\n'\n","  for i in indexes:\n","    dataset_copy.pop(i)\n","  few_shot_learning_examples = few_shot_learning_examples + \"sentence:\"\n","  return few_shot_learning_examples"]},{"cell_type":"code","execution_count":493,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":438,"status":"ok","timestamp":1676233279365,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"lXnnAhJM4eUC","outputId":"354fa579-bf2a-4e66-aa4f-aecc8acc6f52"},"outputs":[{"name":"stdout","output_type":"stream","text":["867 872\n","sentence: it 's a charming and often affecting journey . \n","label: positive\n","sentence: so unassuming and pure of heart , you ca n't help but warmly extend your arms and yell ` safe ! ' \n","label: positive\n","sentence: birthday girl is an amusing joy ride , with some surprisingly violent moments . \n","label: positive\n","sentence: ( chaiken 's ) talent lies in an evocative , accurate observation of a distinctive milieu and in the lively , convincing dialogue she creates for her characters . \n","label: positive\n","sentence: `` the time machine '' is a movie that has no interest in itself . \n","label: negative\n","sentence:\n"]}],"source":["dataset_copy = new_dataset.copy()\n","few_shot_example = create_dataset(indexes)\n","print(len(dataset_copy),len(new_dataset))\n","print(few_shot_example)"]},{"cell_type":"code","execution_count":441,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4,"status":"ok","timestamp":1676232065230,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"qZl1s8otuQb7","outputId":"3213f6c3-374c-481f-d616-5851e4a1071b"},"outputs":[{"name":"stdout","output_type":"stream","text":["There are 1 GPU(s) available.\n","We will use the GPU: Tesla T4\n"]}],"source":["if torch.cuda.is_available():     \n","    device = torch.device(\"cuda\")\n","\n","    print('There are %d GPU(s) available.' % torch.cuda.device_count())\n","    print('We will use the GPU:', torch.cuda.get_device_name(0))\n","\n","else:\n","    print('No GPU available, using the CPU instead.')\n","    device = torch.device(\"cpu\")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"9-BV0UrJuRxA"},"outputs":[],"source":["model = AutoModelForSeq2SeqLM.from_pretrained('google/flan-t5-base')\n","model.cuda()"]},{"cell_type":"code","execution_count":494,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":48127,"status":"ok","timestamp":1676233331926,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"fTa23zkmuZLk","outputId":"b4ea7d5c-b824-45ee-b2ae-88158dbff2c3"},"outputs":[{"name":"stderr","output_type":"stream","text":["100%|██████████| 867/867 [00:48<00:00, 18.06it/s]\n"]}],"source":["pred = create_predictions(dataset_copy)"]},{"cell_type":"code","execution_count":495,"metadata":{"executionInfo":{"elapsed":440,"status":"ok","timestamp":1676233335166,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"h2cQWCXZOUv5"},"outputs":[],"source":["predictions = pred[0]\n","expected = pred[1]"]},{"cell_type":"code","execution_count":497,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":570,"status":"ok","timestamp":1676234098769,"user":{"displayName":"Szymon Jadczak","userId":"16229243011212847322"},"user_tz":-60},"id":"dMslr0Lhw3Hs","outputId":"3b8ddae0-c738-4528-9fc1-9159538a3051"},"outputs":[{"data":{"text/plain":["0.903114186851211"]},"execution_count":497,"metadata":{},"output_type":"execute_result"}],"source":["accuracy_score(expected,predictions)"]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyNGaytftjGZzg/sqa8hRU3s","provenance":[]},"gpuClass":"standard","kernelspec":{"display_name":"Python 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