Model backlog/Train/172-Tweet-Train-5Fold-roBERTa base no QA sentiment head2.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.6"},"colab":{"name":"172-Tweet-Train-5Fold-roBERTa base no QA sentiment head2.ipynb","provenance":[],"collapsed_sections":[]},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"kA4Pu2sPr_eG","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":306},"outputId":"220dd557-db86-4778-f355-b55ab37eb5e2","executionInfo":{"status":"ok","timestamp":1590236343448,"user_tz":180,"elapsed":5861,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["!nvidia-smi"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Sat May 23 12:18:59 2020       \n","+-----------------------------------------------------------------------------+\n","| NVIDIA-SMI 440.82       Driver Version: 418.67       CUDA Version: 10.1     |\n","|-------------------------------+----------------------+----------------------+\n","| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n","| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n","|===============================+======================+======================|\n","|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\n","| N/A   35C    P0    27W / 250W |      0MiB / 16280MiB |      0%      Default |\n","+-------------------------------+----------------------+----------------------+\n","                                                                               \n","+-----------------------------------------------------------------------------+\n","| Processes:                                                       GPU Memory |\n","|  GPU       PID   Type   Process name                             Usage      |\n","|=============================================================================|\n","|  No running processes found                                                 |\n","+-----------------------------------------------------------------------------+\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"rOXNne0OoLTd","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":102},"outputId":"77379e42-7df5-4876-a9eb-a58604c3d871","executionInfo":{"status":"ok","timestamp":1590236359371,"user_tz":180,"elapsed":14539,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["!pip --quiet install transformers\n","!pip --quiet install tokenizers"],"execution_count":2,"outputs":[{"output_type":"stream","text":["\u001b[K     |████████████████████████████████| 665kB 2.7MB/s \n","\u001b[K     |████████████████████████████████| 3.8MB 13.2MB/s \n","\u001b[K     |████████████████████████████████| 1.1MB 27.5MB/s \n","\u001b[K     |████████████████████████████████| 890kB 52.3MB/s \n","\u001b[?25h  Building wheel for sacremoses (setup.py) ... \u001b[?25l\u001b[?25hdone\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"htKChfMHoYRb","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":122},"outputId":"ce885d7a-71ac-444a-c0cf-986a6e93153a","executionInfo":{"status":"ok","timestamp":1590236380374,"user_tz":180,"elapsed":34050,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":3,"outputs":[{"output_type":"stream","text":["Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n","\n","Enter your authorization code:\n","··········\n","Mounted at /content/drive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"xtDZkoyzod_S","colab_type":"code","colab":{}},"source":["!cp -r '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Scripts/.' ."],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"38KKgQn7owCr","colab_type":"code","colab":{}},"source":["COLAB_BASE_PATH = '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/'\n","MODEL_BASE_PATH = COLAB_BASE_PATH + 'Models/Files/172-roBERTa_base/'\n","\n","import os\n","os.mkdir(MODEL_BASE_PATH)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"MOE8CNSAnvq-","colab_type":"text"},"source":["## Dependencies"]},{"cell_type":"code","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","id":"x48gxo3vnvrA","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":71},"outputId":"33d14d79-a20b-4a33-9a37-989a7928a21e","executionInfo":{"status":"ok","timestamp":1590236392126,"user_tz":180,"elapsed":10782,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["import json, warnings, shutil\n","from scripts_step_lr_schedulers import *\n","from tweet_utility_scripts import *\n","from tweet_utility_preprocess_roberta_scripts_aux import *\n","import tweet_utility_preprocess_roberta_scripts_text as preprocess_text\n","from transformers import TFRobertaModel, RobertaConfig\n","from tokenizers import ByteLevelBPETokenizer\n","from tensorflow.keras.models import Model\n","from tensorflow.keras import optimizers, metrics, losses, layers\n","\n","SEED = 0\n","seed_everything(SEED)\n","warnings.filterwarnings(\"ignore\")"],"execution_count":6,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n","  import pandas.util.testing as tm\n"],"name":"stderr"}]},{"cell_type":"markdown","metadata":{"id":"6HW0GQzPnvrF","colab_type":"text"},"source":["# Load data"]},{"cell_type":"code","metadata":{"id":"jS858zlQNNCs","colab_type":"code","colab":{}},"source":["# Unzip files\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_96/no_qa_fold_1.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_96/no_qa_fold_2.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_96/no_qa_fold_3.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_96/no_qa_fold_4.tar.gz'\n","!tar -xf '/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Data/complete_96/no_qa_fold_5.tar.gz'"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_kg_hide-input":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","id":"hVhA98wenvrG","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":513},"outputId":"d0f1aaea-672d-43e7-b527-4044aebe40a1","executionInfo":{"status":"ok","timestamp":1590236409155,"user_tz":180,"elapsed":24320,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["database_base_path = COLAB_BASE_PATH + 'Data/complete_96/'\n","k_fold = pd.read_csv(database_base_path + '5-fold.csv')\n","display(k_fold.head())"],"execution_count":8,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>textID</th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>sentiment</th>\n","      <th>jaccard</th>\n","      <th>text_len</th>\n","      <th>text_wordCnt</th>\n","      <th>text_tokenCnt</th>\n","      <th>selected_text_len</th>\n","      <th>selected_text_wordCnt</th>\n","      <th>selected_text_tokenCnt</th>\n","      <th>fold_1</th>\n","      <th>fold_2</th>\n","      <th>fold_3</th>\n","      <th>fold_4</th>\n","      <th>fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>cb774db0d1</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>35</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>35</td>\n","      <td>7</td>\n","      <td>10</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>549e992a42</td>\n","      <td>sooo sad i will miss you here in san diego!!!</td>\n","      <td>sooo sad</td>\n","      <td>negative</td>\n","      <td>0.200000</td>\n","      <td>45</td>\n","      <td>10</td>\n","      <td>13</td>\n","      <td>8</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>088c60f138</td>\n","      <td>my boss is bullying me...</td>\n","      <td>bullying me</td>\n","      <td>negative</td>\n","      <td>0.166667</td>\n","      <td>25</td>\n","      <td>5</td>\n","      <td>6</td>\n","      <td>11</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>9642c003ef</td>\n","      <td>what interview! leave me alone</td>\n","      <td>leave me alone</td>\n","      <td>negative</td>\n","      <td>0.600000</td>\n","      <td>30</td>\n","      <td>5</td>\n","      <td>6</td>\n","      <td>14</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>train</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>358bd9e861</td>\n","      <td>sons of ****, why couldn`t they put them on th...</td>\n","      <td>sons of ****,</td>\n","      <td>negative</td>\n","      <td>0.214286</td>\n","      <td>74</td>\n","      <td>14</td>\n","      <td>17</td>\n","      <td>13</td>\n","      <td>3</td>\n","      <td>4</td>\n","      <td>train</td>\n","      <td>train</td>\n","      <td>validation</td>\n","      <td>train</td>\n","      <td>train</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       textID  ... fold_5\n","0  cb774db0d1  ...  train\n","1  549e992a42  ...  train\n","2  088c60f138  ...  train\n","3  9642c003ef  ...  train\n","4  358bd9e861  ...  train\n","\n","[5 rows x 16 columns]"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"b0bUTMPynvrM","colab_type":"text"},"source":["# Model parameters"]},{"cell_type":"code","metadata":{"id":"Paexn4ywnvrM","colab_type":"code","colab":{}},"source":["vocab_path = COLAB_BASE_PATH + 'qa-transformers/roberta/roberta-base-vocab.json'\n","merges_path = COLAB_BASE_PATH + 'qa-transformers/roberta/roberta-base-merges.txt'\n","base_path = COLAB_BASE_PATH + 'qa-transformers/roberta/'\n","\n","config = {\n","  \"MAX_LEN\": 96,\n","  \"BATCH_SIZE\": 32,\n","  \"EPOCHS\": 4,\n","  \"LEARNING_RATE\": 3e-5,\n","  \"ES_PATIENCE\": 4,\n","  \"question_size\": 0,\n","  \"N_FOLDS\": 5,\n","  \"base_model_path\": base_path + 'roberta-base-tf_model.h5',\n","  \"config_path\": base_path + 'roberta-base-config.json'\n","}\n","\n","with open(MODEL_BASE_PATH + 'config.json', 'w') as json_file:\n","    json.dump(json.loads(json.dumps(config)), json_file)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"D_8F5nxDnvrW","colab_type":"text"},"source":["# Tokenizer"]},{"cell_type":"code","metadata":{"_kg_hide-output":true,"id":"6qeQlxrDnvrX","colab_type":"code","colab":{}},"source":["tokenizer = ByteLevelBPETokenizer(vocab_file=vocab_path, merges_file=merges_path, \n","                                  lowercase=True, add_prefix_space=True)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"S3FN1pb1nvrb","colab_type":"text"},"source":["## Learning rate schedule"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"id":"XUYfnwPRnvrc","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":403},"outputId":"763b4f1b-d25b-48a7-ab2e-94a5953dd6fd","executionInfo":{"status":"ok","timestamp":1590236419778,"user_tz":180,"elapsed":25600,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["lr_min = 1e-6\n","lr_max = config['LEARNING_RATE']\n","train_size = len(k_fold[k_fold['fold_1'] == 'train'])\n","step_size = train_size // config['BATCH_SIZE']\n","total_steps = config['EPOCHS'] * step_size\n","decay = .9987\n","\n","rng = [i for i in range(0, total_steps, config['BATCH_SIZE'])]\n","y = [exponential_schedule_with_warmup(tf.cast(x, tf.float32), warmup_steps=1, lr_start=lr_max, lr_max=lr_max, lr_min=lr_min, decay=decay) for x in rng]\n","\n","sns.set(style=\"whitegrid\")\n","fig, ax = plt.subplots(figsize=(20, 6))\n","plt.plot(rng, y)\n","print(\"Learning rate schedule: {:.3g} to {:.3g} to {:.3g}\".format(y[0], max(y), y[-1]))"],"execution_count":11,"outputs":[{"output_type":"stream","text":["Learning rate schedule: 3e-05 to 3e-05 to 1e-06\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1440x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"3aHwZDF9nvrR","colab_type":"text"},"source":["# Model"]},{"cell_type":"code","metadata":{"id":"7gIO5wkQnvrS","colab_type":"code","colab":{}},"source":["module_config = RobertaConfig.from_pretrained(config['config_path'], output_hidden_states=False)\n","\n","def model_fn(MAX_LEN):\n","    input_ids = layers.Input(shape=(MAX_LEN,), dtype=tf.int32, name='input_ids')\n","    attention_mask = layers.Input(shape=(MAX_LEN,), dtype=tf.int32, name='attention_mask')\n","    input_sentiment = layers.Input(shape=(3,), dtype=tf.float32, name='input_sentiment')\n","    \n","    base_model = TFRobertaModel.from_pretrained(config['base_model_path'], config=module_config, name=\"base_model\")\n","    last_hidden_state, _ = base_model({'input_ids': input_ids, 'attention_mask': attention_mask})\n","    \n","    x_start_negative = layers.Dropout(.1)(last_hidden_state)\n","    x_start_negative = layers.Dense(1)(x_start_negative)\n","    x_start_negative = layers.Flatten()(x_start_negative)\n","    y_start_negative = layers.Activation('softmax', name='y_start_negative')(x_start_negative)\n","    y_start_negative = layers.Multiply()([y_start_negative, input_sentiment[:,0]])\n","    \n","    x_start_neutral = layers.Dropout(.1)(last_hidden_state)\n","    x_start_neutral = layers.Dense(1)(x_start_neutral)\n","    x_start_neutral = layers.Flatten()(x_start_neutral)\n","    y_start_neutral = layers.Activation('softmax', name='y_start_neutral')(x_start_neutral)\n","    y_start_neutral = layers.Multiply()([y_start_neutral, input_sentiment[:,1]])\n","    \n","    x_start_positive = layers.Dropout(.1)(last_hidden_state)\n","    x_start_positive = layers.Dense(1)(x_start_positive)\n","    x_start_positive = layers.Flatten()(x_start_positive)\n","    y_start_positive = layers.Activation('softmax', name='y_start_positive')(x_start_positive)\n","    y_start_positive = layers.Multiply()([y_start_positive, input_sentiment[:,2]])\n","\n","    y_start_sum = layers.Add(name='y_start_avg')([y_start_negative, y_start_neutral, y_start_positive])\n","    \n","    x_start = layers.Dropout(.1)(last_hidden_state)\n","    x_start = layers.Dense(1)(x_start)\n","    x_start = layers.Flatten()(x_start)\n","    y_start = layers.Activation('softmax')(x_start)\n","    y_start = layers.Average(name='y_start')([y_start, y_start_sum])\n","\n","    x_end_negative = layers.Dropout(.1)(last_hidden_state)\n","    x_end_negative = layers.Dense(1)(x_end_negative)\n","    x_end_negative = layers.Flatten()(x_end_negative)\n","    y_end_negative = layers.Activation('softmax', name='y_end_negative')(x_end_negative)\n","    y_end_negative = layers.Multiply()([y_end_negative, input_sentiment[:,0]])\n","\n","    x_end_neutral = layers.Dropout(.1)(last_hidden_state)\n","    x_end_neutral = layers.Dense(1)(x_end_neutral)\n","    x_end_neutral = layers.Flatten()(x_end_neutral)\n","    y_end_neutral = layers.Activation('softmax', name='y_end_neutral')(x_end_neutral)\n","    y_end_neutral = layers.Multiply()([y_end_neutral, input_sentiment[:,1]])\n","\n","    x_end_positive = layers.Dropout(.1)(last_hidden_state)\n","    x_end_positive = layers.Dense(1)(x_end_positive)\n","    x_end_positive = layers.Flatten()(x_end_positive)\n","    y_end_positive = layers.Activation('softmax', name='y_end_positive')(x_end_positive)\n","    y_end_positive = layers.Multiply()([y_end_positive, input_sentiment[:,2]])\n","\n","    y_end_sum = layers.Add(name='y_end_avg')([y_end_negative, y_end_neutral, y_end_positive])\n","\n","    x_end = layers.Dropout(.1)(last_hidden_state)\n","    x_end = layers.Dense(1)(x_end)\n","    x_end = layers.Flatten()(x_end)\n","    y_end = layers.Activation('softmax')(x_end)\n","    y_end = layers.Average(name='y_end')([y_end, y_end_sum])\n","    \n","    model = Model(inputs=[input_ids, attention_mask, input_sentiment], outputs=[y_start, y_end])\n","    \n","    return model"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"jy24FlCgnvrj","colab_type":"text"},"source":["# Train"]},{"cell_type":"code","metadata":{"id":"zNWpgFF60lj_","colab_type":"code","colab":{}},"source":["def get_training_dataset(x_train, y_train, batch_size, buffer_size, seed=0):\n","    dataset = tf.data.Dataset.from_tensor_slices(({'input_ids': x_train[0], 'attention_mask': x_train[1], 'input_sentiment': x_train[2]}, \n","                                                  {'y_start': y_train[0],'y_end': y_train[1]}))\n","    dataset = dataset.repeat()\n","    dataset = dataset.shuffle(2048, seed=seed)\n","    dataset = dataset.batch(batch_size, drop_remainder=True)\n","    dataset = dataset.prefetch(buffer_size)\n","    return dataset\n","\n","def get_validation_dataset(x_valid, y_valid, batch_size, buffer_size, repeated=False, seed=0):\n","    dataset = tf.data.Dataset.from_tensor_slices(({'input_ids': x_valid[0], 'attention_mask': x_valid[1], 'input_sentiment': x_valid[2]}, \n","                                                  {'y_start': y_valid[0],'y_end': y_valid[1]}))\n","    if repeated:\n","        dataset = dataset.repeat()\n","        dataset = dataset.shuffle(2048, seed=seed)\n","    dataset = dataset.batch(batch_size, drop_remainder=True)\n","    dataset = dataset.cache()\n","    dataset = dataset.prefetch(buffer_size)\n","    return dataset\n","\n","def get_test_dataset(x_test, batch_size):\n","    dataset = tf.data.Dataset.from_tensor_slices({'input_ids': x_test[0], 'attention_mask': x_test[1], 'input_sentiment': x_test[2]})\n","    dataset = dataset.batch(batch_size)\n","    return dataset"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"id":"RU2sa648nvrj","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":1000},"outputId":"168d5cc7-dc3f-4818-dc40-aadb948b6afc","executionInfo":{"status":"ok","timestamp":1590243442026,"user_tz":180,"elapsed":6815461,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["AUTO = tf.data.experimental.AUTOTUNE\n","strategy = tf.distribute.get_strategy()\n","k_fold_best = k_fold.copy()\n","history_list = []\n","\n","for n_fold in range(config['N_FOLDS']):\n","    n_fold +=1\n","    print('\\nFOLD: %d' % (n_fold))\n","\n","    # Load data\n","    base_data_path = 'no_qa_fold_%d/' % (n_fold)\n","    x_train = np.load(base_data_path + 'x_train.npy')\n","    x_train_aux2 = np.load(base_data_path + 'x_train_aux2.npy')\n","    y_train = np.load(base_data_path + 'y_train.npy')\n","    x_valid = np.load(base_data_path + 'x_valid.npy')\n","    x_valid_aux2 = np.load(base_data_path + 'x_valid_aux2.npy')\n","    y_valid = np.load(base_data_path + 'y_valid.npy')\n","    \n","    step_size = x_train.shape[1] // config['BATCH_SIZE']\n","    valid_step_size = x_valid.shape[1] // config['BATCH_SIZE']\n","\n","    # Build TF datasets\n","    train_dist_ds = strategy.experimental_distribute_dataset(get_training_dataset((*x_train, x_train_aux2), y_train, config['BATCH_SIZE'], AUTO, seed=SEED))\n","    valid_dist_ds = strategy.experimental_distribute_dataset(get_validation_dataset((*x_valid, x_valid_aux2), y_valid, config['BATCH_SIZE'], AUTO, repeated=True, seed=SEED))\n","    train_data_iter = iter(train_dist_ds)\n","    valid_data_iter = iter(valid_dist_ds)\n","    \n","    # Step functions\n","    @tf.function\n","    def train_step(data_iter):\n","        def train_step_fn(x, y):\n","            with tf.GradientTape() as tape:\n","                probabilities = model(x, training=True)\n","                loss_start = loss_fn(y['y_start'], probabilities[0])\n","                loss_end = loss_fn(y['y_end'], probabilities[1])\n","                loss = tf.math.add(loss_start, loss_end)\n","            grads = tape.gradient(loss, model.trainable_variables)\n","            optimizer.apply_gradients(zip(grads, model.trainable_variables))\n","            # update metrics\n","            train_loss.update_state(loss)\n","            train_loss_start.update_state(loss_start)\n","            train_loss_end.update_state(loss_end)\n","        for _ in tf.range(step_size):\n","            strategy.experimental_run_v2(train_step_fn, next(data_iter))\n","\n","    @tf.function\n","    def valid_step(data_iter):\n","        def valid_step_fn(x, y):\n","            probabilities = model(x, training=False)\n","            loss_start = loss_fn(y['y_start'], probabilities[0])\n","            loss_end = loss_fn(y['y_end'], probabilities[1])\n","            loss = tf.math.add(loss_start, loss_end)\n","            # update metrics\n","            valid_loss.update_state(loss)\n","            valid_loss_start.update_state(loss_start)\n","            valid_loss_end.update_state(loss_end)\n","        for _ in tf.range(valid_step_size):\n","            strategy.experimental_run_v2(valid_step_fn, next(data_iter))\n","\n","    # Train model\n","    model_path = 'model_fold_%d.h5' % (n_fold)\n","    model = model_fn(config['MAX_LEN'])\n","    optimizer = optimizers.Adam(learning_rate=lambda: exponential_schedule_with_warmup(tf.cast(optimizer.iterations, tf.float32), warmup_steps=1, \n","                                                                                       lr_start=lr_max, lr_max=lr_max, lr_min=lr_min, decay=decay))\n","    loss_fn = losses.categorical_crossentropy\n","    train_loss = metrics.Sum()\n","    valid_loss = metrics.Sum()\n","    train_loss_start = metrics.Sum()\n","    valid_loss_start = metrics.Sum()\n","    train_loss_end = metrics.Sum()\n","    valid_loss_end = metrics.Sum()\n","        \n","    metrics_dict = {'loss': train_loss, 'loss_start': train_loss_start, 'loss_end': train_loss_end, \n","                    'val_loss': valid_loss, 'val_loss_start': valid_loss_start, 'val_loss_end': valid_loss_end}\n","        \n","    history = custom_fit(model, metrics_dict, train_step, valid_step, train_data_iter, valid_data_iter, \n","                         step_size, valid_step_size, config['BATCH_SIZE'], config['EPOCHS'], config['ES_PATIENCE'], \n","                         (MODEL_BASE_PATH + model_path), save_last=False)\n","    \n","    history_list.append(history)\n","    model.save_weights(MODEL_BASE_PATH +'last_' + model_path)\n","    \n","    # Make predictions (last model)\n","    x_train = np.load(base_data_path + 'x_train.npy')\n","    x_valid = np.load(base_data_path + 'x_valid.npy')\n","    train_preds = model.predict(get_test_dataset((*x_train, x_train_aux2), config['BATCH_SIZE']))\n","    valid_preds = model.predict(get_test_dataset((*x_valid, x_valid_aux2), config['BATCH_SIZE']))\n","    \n","    k_fold.loc[k_fold['fold_%d' % (n_fold)] == 'train', 'start_fold_%d' % (n_fold)] = train_preds[0].argmax(axis=-1)\n","    k_fold.loc[k_fold['fold_%d' % (n_fold)] == 'train', 'end_fold_%d' % (n_fold)] = train_preds[1].argmax(axis=-1)\n","    k_fold.loc[k_fold['fold_%d' % (n_fold)] == 'validation', 'start_fold_%d' % (n_fold)] = valid_preds[0].argmax(axis=-1)\n","    k_fold.loc[k_fold['fold_%d' % (n_fold)] == 'validation', 'end_fold_%d' % (n_fold)] = valid_preds[1].argmax(axis=-1)\n","    \n","    k_fold['end_fold_%d' % (n_fold)] = k_fold['end_fold_%d' % (n_fold)].astype(int)\n","    k_fold['start_fold_%d' % (n_fold)] = k_fold['start_fold_%d' % (n_fold)].astype(int)\n","    k_fold['end_fold_%d' % (n_fold)].clip(0, k_fold['text_len'], inplace=True)\n","    k_fold['start_fold_%d' % (n_fold)].clip(0, k_fold['end_fold_%d' % (n_fold)], inplace=True)\n","    k_fold['prediction_fold_%d' % (n_fold)] = k_fold.apply(lambda x: preprocess_text.decode(x['start_fold_%d' % (n_fold)], x['end_fold_%d' % (n_fold)], x['text'], tokenizer), axis=1)\n","    k_fold['prediction_fold_%d' % (n_fold)].fillna(k_fold[\"text\"], inplace=True)\n","    k_fold['jaccard_fold_%d' % (n_fold)] = k_fold.apply(lambda x: jaccard(x['selected_text'], x['prediction_fold_%d' % (n_fold)]), axis=1)\n","\n","    # Make predictions (best model)\n","    model.load_weights(MODEL_BASE_PATH + model_path)\n","    train_preds = model.predict(get_test_dataset((*x_train, x_train_aux2), config['BATCH_SIZE']))\n","    valid_preds = model.predict(get_test_dataset((*x_valid, x_valid_aux2), config['BATCH_SIZE']))\n","    \n","    k_fold_best.loc[k_fold_best['fold_%d' % (n_fold)] == 'train', 'start_fold_%d' % (n_fold)] = train_preds[0].argmax(axis=-1)\n","    k_fold_best.loc[k_fold_best['fold_%d' % (n_fold)] == 'train', 'end_fold_%d' % (n_fold)] = train_preds[1].argmax(axis=-1)\n","    k_fold_best.loc[k_fold_best['fold_%d' % (n_fold)] == 'validation', 'start_fold_%d' % (n_fold)] = valid_preds[0].argmax(axis=-1)\n","    k_fold_best.loc[k_fold_best['fold_%d' % (n_fold)] == 'validation', 'end_fold_%d' % (n_fold)] = valid_preds[1].argmax(axis=-1)\n","    \n","    k_fold_best['end_fold_%d' % (n_fold)] = k_fold_best['end_fold_%d' % (n_fold)].astype(int)\n","    k_fold_best['start_fold_%d' % (n_fold)] = k_fold_best['start_fold_%d' % (n_fold)].astype(int)\n","    k_fold_best['end_fold_%d' % (n_fold)].clip(0, k_fold_best['text_len'], inplace=True)\n","    k_fold_best['start_fold_%d' % (n_fold)].clip(0, k_fold_best['end_fold_%d' % (n_fold)], inplace=True)\n","    k_fold_best['prediction_fold_%d' % (n_fold)] = k_fold_best.apply(lambda x: preprocess_text.decode(x['start_fold_%d' % (n_fold)], x['end_fold_%d' % (n_fold)], x['text'], tokenizer), axis=1)\n","    k_fold_best['prediction_fold_%d' % (n_fold)].fillna(k_fold_best[\"text\"], inplace=True)\n","    k_fold_best['jaccard_fold_%d' % (n_fold)] = k_fold_best.apply(lambda x: jaccard(x['selected_text'], x['prediction_fold_%d' % (n_fold)]), axis=1)"],"execution_count":14,"outputs":[{"output_type":"stream","text":["\n","FOLD: 1\n","Train for 687 steps, validate for 171 steps\n","WARNING:tensorflow:From <ipython-input-14-51144f6245ed>:44: StrategyBase.experimental_run_v2 (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.\n","Instructions for updating:\n","renamed to `run`\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","\n","EPOCH 1/4\n","time: 276.2s loss: 2.2556 loss_start: 1.1289 loss_end: 1.1267 val_loss: 1.8604 val_loss_start: 0.9535 val_loss_end: 0.9069\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_1.h5\"\n","\n","EPOCH 2/4\n","time: 265.7s loss: 1.7725 loss_start: 0.9066 loss_end: 0.8659 val_loss: 1.7551 val_loss_start: 0.9159 val_loss_end: 0.8392\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_1.h5\"\n","\n","EPOCH 3/4\n","time: 268.4s loss: 1.6549 loss_start: 0.8484 loss_end: 0.8065 val_loss: 1.7654 val_loss_start: 0.9005 val_loss_end: 0.8649\n","\n","EPOCH 4/4\n","time: 263.8s loss: 1.5871 loss_start: 0.8209 loss_end: 0.7662 val_loss: 1.7645 val_loss_start: 0.8995 val_loss_end: 0.8650\n","Training finished\n","\n","FOLD: 2\n","Train for 687 steps, validate for 171 steps\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","\n","EPOCH 1/4\n","time: 276.5s loss: 2.4128 loss_start: 1.1607 loss_end: 1.2521 val_loss: 2.0440 val_loss_start: 0.9922 val_loss_end: 1.0518\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_2.h5\"\n","\n","EPOCH 2/4\n","time: 267.0s loss: 1.9010 loss_start: 0.9492 loss_end: 0.9519 val_loss: 1.8913 val_loss_start: 0.9533 val_loss_end: 0.9380\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_2.h5\"\n","\n","EPOCH 3/4\n","time: 268.4s loss: 1.7704 loss_start: 0.8873 loss_end: 0.8831 val_loss: 1.9280 val_loss_start: 0.9782 val_loss_end: 0.9497\n","\n","EPOCH 4/4\n","time: 264.7s loss: 1.7139 loss_start: 0.8655 loss_end: 0.8484 val_loss: 1.9152 val_loss_start: 0.9448 val_loss_end: 0.9704\n","Training finished\n","\n","FOLD: 3\n","Train for 687 steps, validate for 171 steps\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","\n","EPOCH 1/4\n","time: 276.9s loss: 2.3220 loss_start: 1.1481 loss_end: 1.1739 val_loss: 1.8798 val_loss_start: 0.9355 val_loss_end: 0.9443\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_3.h5\"\n","\n","EPOCH 2/4\n","time: 266.2s loss: 1.8035 loss_start: 0.9242 loss_end: 0.8793 val_loss: 1.7689 val_loss_start: 0.8960 val_loss_end: 0.8729\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_3.h5\"\n","\n","EPOCH 3/4\n","time: 269.0s loss: 1.6697 loss_start: 0.8621 loss_end: 0.8076 val_loss: 1.7421 val_loss_start: 0.8883 val_loss_end: 0.8537\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_3.h5\"\n","\n","EPOCH 4/4\n","time: 268.4s loss: 1.6187 loss_start: 0.8370 loss_end: 0.7818 val_loss: 1.7830 val_loss_start: 0.9056 val_loss_end: 0.8774\n","Training finished\n","\n","FOLD: 4\n","Train for 687 steps, validate for 171 steps\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","\n","EPOCH 1/4\n","time: 276.6s loss: 2.3815 loss_start: 1.1491 loss_end: 1.2325 val_loss: 1.9602 val_loss_start: 0.9831 val_loss_end: 0.9771\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_4.h5\"\n","\n","EPOCH 2/4\n","time: 266.7s loss: 1.8551 loss_start: 0.9234 loss_end: 0.9318 val_loss: 1.8524 val_loss_start: 0.9397 val_loss_end: 0.9126\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_4.h5\"\n","\n","EPOCH 3/4\n","time: 269.0s loss: 1.7497 loss_start: 0.8807 loss_end: 0.8690 val_loss: 1.8200 val_loss_start: 0.9381 val_loss_end: 0.8819\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_4.h5\"\n","\n","EPOCH 4/4\n","time: 268.5s loss: 1.6995 loss_start: 0.8548 loss_end: 0.8447 val_loss: 1.8439 val_loss_start: 0.9537 val_loss_end: 0.8902\n","Training finished\n","\n","FOLD: 5\n","Train for 687 steps, validate for 171 steps\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","WARNING:tensorflow:Gradients do not exist for variables ['base_model/roberta/pooler/dense/kernel:0', 'base_model/roberta/pooler/dense/bias:0'] when minimizing the loss.\n","\n","EPOCH 1/4\n","time: 277.1s loss: 2.2584 loss_start: 1.1275 loss_end: 1.1309 val_loss: 1.8163 val_loss_start: 0.9232 val_loss_end: 0.8931\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_5.h5\"\n","\n","EPOCH 2/4\n","time: 267.0s loss: 1.7936 loss_start: 0.9188 loss_end: 0.8748 val_loss: 1.7788 val_loss_start: 0.9088 val_loss_end: 0.8700\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_5.h5\"\n","\n","EPOCH 3/4\n","time: 268.6s loss: 1.6993 loss_start: 0.8752 loss_end: 0.8241 val_loss: 1.7808 val_loss_start: 0.9194 val_loss_end: 0.8614\n","\n","EPOCH 4/4\n","time: 264.8s loss: 1.6378 loss_start: 0.8431 loss_end: 0.7948 val_loss: 1.7342 val_loss_start: 0.8896 val_loss_end: 0.8446\n","Saved model weights at \"/content/drive/My Drive/Colab Notebooks/Tweet Sentiment Extraction/Models/Files/172-roBERTa_base/model_fold_5.h5\"\n","Training finished\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"_59x5WnGnvro","colab_type":"text"},"source":["# Model loss graph"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"id":"Tlq60Zvenvro","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":1000},"outputId":"58c950ac-db23-4377-9869-6dd99180aa6a","executionInfo":{"status":"ok","timestamp":1590243444486,"user_tz":180,"elapsed":6817075,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["for n_fold in range(config['N_FOLDS']):\n","    print('Fold: %d' % (n_fold+1))\n","    plot_metrics(history_list[n_fold])"],"execution_count":15,"outputs":[{"output_type":"stream","text":["Fold: 1\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Fold: 2\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Fold: 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size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Fold: 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size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Fold: 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size 1440x1080 with 3 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"MvzO_AjPnvrt","colab_type":"text"},"source":["# Model evaluation (last model)"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"id":"ELe26ujlnvrt","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":588},"outputId":"138f4176-a3d3-4b7e-c375-e51d8d566772","executionInfo":{"status":"ok","timestamp":1590243448062,"user_tz":180,"elapsed":6819976,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["display(evaluate_model_kfold(k_fold, config['N_FOLDS']).style.applymap(color_map))"],"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    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#T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col8 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col9 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col10 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col11 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col12 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col0 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col1 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col2 {\n","            color:  red;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col3 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col4 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col5 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col6 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col7 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col8 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col9 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col10 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col11 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col12 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col0 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col1 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col2 {\n","            color:  red;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col3 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col4 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col5 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col6 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col7 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col8 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col9 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col10 {\n","            color:  orange;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col11 {\n","            color:  black;\n","        }    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#T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col1 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col2 {\n","            color:  red;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col3 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col4 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col5 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col6 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col7 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col8 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col9 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col10 {\n","            color:  black;\n","        }    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#T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col8 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col9 {\n","            color:  green;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col10 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col11 {\n","            color:  black;\n","        }    #T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col12 {\n","            color:  green;\n","        }</style><table id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.698831</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.674309</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.024521</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.708427</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.677788</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.690055</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.663446</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.700589</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.678540</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.694277</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.665876</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.700805</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.685896</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >Sentiment negative</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col0\" class=\"data row1 col0\" >0.524883</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col1\" class=\"data row1 col1\" >0.479708</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col2\" class=\"data row1 col2\" >0.045176</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.537594</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0.487800</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0.516039</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col6\" class=\"data row1 col6\" >0.462157</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.524557</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col8\" class=\"data row1 col8\" >0.485206</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col9\" class=\"data row1 col9\" >0.519775</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col10\" class=\"data row1 col10\" >0.471706</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col11\" class=\"data row1 col11\" >0.526452</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row1_col12\" class=\"data row1 col12\" >0.491670</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >Sentiment neutral</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0.972392</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0.971215</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col2\" class=\"data row2 col2\" >0.001176</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.976215</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.976819</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0.962315</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col6\" class=\"data row2 col6\" >0.960609</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0.975962</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col8\" class=\"data row2 col8\" >0.976473</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col9\" class=\"data row2 col9\" >0.970699</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col10\" class=\"data row2 col10\" >0.966929</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col11\" class=\"data row2 col11\" >0.976767</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row2_col12\" class=\"data row2 col12\" >0.975246</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >Sentiment positive</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0.502175</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col1\" class=\"data row3 col1\" >0.466139</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col2\" class=\"data row3 col2\" >0.036036</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.516466</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col4\" class=\"data row3 col4\" >0.462505</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0.495189</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0.460833</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0.503453</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col8\" class=\"data row3 col8\" >0.468003</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col9\" class=\"data row3 col9\" >0.494390</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col10\" class=\"data row3 col10\" >0.452067</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col11\" class=\"data row3 col11\" >0.501378</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row3_col12\" class=\"data row3 col12\" >0.487289</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >0 <= text wordCnt < 3</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0.903420</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col1\" class=\"data row4 col1\" >0.899703</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col2\" class=\"data row4 col2\" >0.003717</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.907051</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0.884328</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col5\" class=\"data row4 col5\" >0.901502</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0.909492</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.897812</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col8\" class=\"data row4 col8\" >0.914698</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col9\" class=\"data row4 col9\" >0.907273</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col10\" class=\"data row4 col10\" >0.887821</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col11\" class=\"data row4 col11\" >0.903462</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row4_col12\" class=\"data row4 col12\" >0.902174</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >3 <= text wordCnt < 10</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col0\" class=\"data row5 col0\" >0.752641</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0.738503</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0.014138</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.761854</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.733791</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col5\" class=\"data row5 col5\" >0.747679</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0.736569</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col7\" class=\"data row5 col7\" >0.750927</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col8\" class=\"data row5 col8\" >0.741774</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col9\" class=\"data row5 col9\" >0.751149</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col10\" class=\"data row5 col10\" >0.731275</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col11\" class=\"data row5 col11\" >0.751597</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row5_col12\" class=\"data row5 col12\" >0.749106</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >10 <= text wordCnt < 30</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col0\" class=\"data row6 col0\" >0.662655</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col1\" class=\"data row6 col1\" >0.631974</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col2\" class=\"data row6 col2\" >0.030681</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.672907</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.639149</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0.651250</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col6\" class=\"data row6 col6\" >0.617383</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col7\" class=\"data row6 col7\" >0.666203</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col8\" class=\"data row6 col8\" >0.638129</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col9\" class=\"data row6 col9\" >0.656433</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col10\" class=\"data row6 col10\" >0.621552</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col11\" class=\"data row6 col11\" >0.666482</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row6_col12\" class=\"data row6 col12\" >0.643655</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >30 <= text wordCnt < 100</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0.619968</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0.579406</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col2\" class=\"data row7 col2\" >0.040562</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.623336</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.650746</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col5\" class=\"data row7 col5\" >0.627971</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col6\" class=\"data row7 col6\" >0.483059</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0.619588</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col8\" class=\"data row7 col8\" >0.574622</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col9\" class=\"data row7 col9\" >0.627065</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col10\" class=\"data row7 col10\" >0.506414</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col11\" class=\"data row7 col11\" >0.601880</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row7_col12\" class=\"data row7 col12\" >0.682187</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >0 <= selected text wordCnt < 3</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col0\" class=\"data row8 col0\" >0.544202</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col1\" class=\"data row8 col1\" >0.500615</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col2\" class=\"data row8 col2\" >0.043587</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.561160</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col4\" class=\"data row8 col4\" >0.502205</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col5\" class=\"data row8 col5\" >0.542744</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col6\" class=\"data row8 col6\" >0.496190</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col7\" class=\"data row8 col7\" >0.537721</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col8\" class=\"data row8 col8\" >0.496083</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col9\" class=\"data row8 col9\" >0.527011</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col10\" class=\"data row8 col10\" >0.479209</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col11\" class=\"data row8 col11\" >0.552373</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row8_col12\" class=\"data row8 col12\" >0.529385</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >3 <= selected text wordCnt < 10</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col0\" class=\"data row9 col0\" >0.702556</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col1\" class=\"data row9 col1\" >0.682190</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col2\" class=\"data row9 col2\" >0.020366</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.708008</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.685367</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.692061</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col6\" class=\"data row9 col6\" >0.668426</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col7\" class=\"data row9 col7\" >0.709075</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col8\" class=\"data row9 col8\" >0.689610</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col9\" class=\"data row9 col9\" >0.706784</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col10\" class=\"data row9 col10\" >0.682790</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col11\" class=\"data row9 col11\" >0.696852</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row9_col12\" class=\"data row9 col12\" >0.684754</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >10 <= selected text wordCnt < 30</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col0\" class=\"data row10 col0\" >0.880386</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col1\" class=\"data row10 col1\" >0.873639</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col2\" class=\"data row10 col2\" >0.006747</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.886654</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col4\" class=\"data row10 col4\" >0.878800</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col5\" class=\"data row10 col5\" >0.865476</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col6\" class=\"data row10 col6\" >0.856482</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col7\" class=\"data row10 col7\" >0.885607</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col8\" class=\"data row10 col8\" >0.885980</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col9\" class=\"data row10 col9\" >0.879042</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col10\" class=\"data row10 col10\" >0.872621</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col11\" class=\"data row10 col11\" >0.885152</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row10_col12\" class=\"data row10 col12\" >0.874315</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >30 <= selected text wordCnt < 100</th>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col0\" class=\"data row11 col0\" >0.897090</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col1\" class=\"data row11 col1\" >0.876429</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col2\" class=\"data row11 col2\" >0.020661</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.909041</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.893070</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col5\" class=\"data row11 col5\" >0.894404</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col6\" class=\"data row11 col6\" >0.797992</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col7\" class=\"data row11 col7\" >0.902189</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col8\" class=\"data row11 col8\" >0.908788</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col9\" class=\"data row11 col9\" >0.904783</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col10\" class=\"data row11 col10\" >0.835385</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col11\" class=\"data row11 col11\" >0.875032</td>\n","                        <td id=\"T_2132cc7e_9d00_11ea_8965_0242ac1c0002row11_col12\" class=\"data row11 col12\" >0.946910</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f5aeea7c438>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"xxbg-_R_p2dE","colab_type":"text"},"source":["# Model evaluation (best model)"]},{"cell_type":"code","metadata":{"id":"KgsapEFup3zY","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":588},"outputId":"6bdd5a9f-ffbf-4e77-ed62-9873b896bf60","executionInfo":{"status":"ok","timestamp":1590243452088,"user_tz":180,"elapsed":6822350,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["display(evaluate_model_kfold(k_fold_best, config['N_FOLDS']).style.applymap(color_map))"],"execution_count":17,"outputs":[{"output_type":"display_data","data":{"text/html":["<style  type=\"text/css\" >\n","    #T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col0 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col1 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col2 {\n","            color:  red;\n","        }    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#T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col12 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col0 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col1 {\n","            color:  orange;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col2 {\n","            color:  red;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col3 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col4 {\n","            color:  orange;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col5 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col6 {\n","            color:  orange;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col7 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col8 {\n","            color:  orange;\n","        }    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#T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col6 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col7 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col8 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col9 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col10 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col11 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col12 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col0 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col1 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col2 {\n","            color:  red;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col3 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col4 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col5 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col6 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col7 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col8 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col9 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col10 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col11 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col12 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col0 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col1 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col2 {\n","            color:  red;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col3 {\n","            color:  green;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col4 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col5 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col6 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col7 {\n","            color:  green;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col8 {\n","            color:  green;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col9 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col10 {\n","            color:  green;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col11 {\n","            color:  black;\n","        }    #T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col12 {\n","            color:  green;\n","        }</style><table id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Train</th>        <th class=\"col_heading level0 col1\" >Valid</th>        <th class=\"col_heading level0 col2\" >Var</th>        <th class=\"col_heading level0 col3\" >Train_fold_1</th>        <th class=\"col_heading level0 col4\" >Valid_fold_1</th>        <th class=\"col_heading level0 col5\" >Train_fold_2</th>        <th class=\"col_heading level0 col6\" >Valid_fold_2</th>        <th class=\"col_heading level0 col7\" >Train_fold_3</th>        <th class=\"col_heading level0 col8\" >Valid_fold_3</th>        <th class=\"col_heading level0 col9\" >Train_fold_4</th>        <th class=\"col_heading level0 col10\" >Valid_fold_4</th>        <th class=\"col_heading level0 col11\" >Train_fold_5</th>        <th class=\"col_heading level0 col12\" >Valid_fold_5</th>    </tr>    <tr>        <th class=\"index_name level0\" >Metric/Jaccard</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n","                <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >Overall</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.694045</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.673935</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.020109</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.699847</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.678611</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.679484</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.660259</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.697354</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col8\" class=\"data row0 col8\" >0.675533</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col9\" class=\"data row0 col9\" >0.692734</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col10\" class=\"data row0 col10\" >0.669378</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col11\" class=\"data row0 col11\" >0.700805</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row0_col12\" class=\"data row0 col12\" >0.685896</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >Sentiment negative</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col0\" class=\"data row1 col0\" >0.515661</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col1\" class=\"data row1 col1\" >0.480213</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col2\" class=\"data row1 col2\" >0.035448</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.527400</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0.489547</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0.493764</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col6\" class=\"data row1 col6\" >0.459060</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.518051</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col8\" class=\"data row1 col8\" >0.480571</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col9\" class=\"data row1 col9\" >0.512637</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col10\" class=\"data row1 col10\" >0.480216</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col11\" class=\"data row1 col11\" >0.526452</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row1_col12\" class=\"data row1 col12\" >0.491670</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >Sentiment neutral</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0.972985</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0.972260</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col2\" class=\"data row2 col2\" >0.000725</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col3\" class=\"data row2 col3\" >0.975804</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.977847</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0.964075</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col6\" class=\"data row2 col6\" >0.961912</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0.976325</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col8\" class=\"data row2 col8\" >0.976515</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col9\" class=\"data row2 col9\" >0.971955</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col10\" class=\"data row2 col10\" >0.969780</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col11\" class=\"data row2 col11\" >0.976767</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row2_col12\" class=\"data row2 col12\" >0.975246</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >Sentiment positive</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0.494444</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col1\" class=\"data row3 col1\" >0.463130</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col2\" class=\"data row3 col2\" >0.031313</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.498769</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col4\" class=\"data row3 col4\" >0.462226</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0.479256</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0.451744</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0.498522</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col8\" class=\"data row3 col8\" >0.462521</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col9\" class=\"data row3 col9\" >0.494293</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col10\" class=\"data row3 col10\" >0.451872</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col11\" class=\"data row3 col11\" >0.501378</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row3_col12\" class=\"data row3 col12\" >0.487289</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >0 <= text wordCnt < 3</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0.902464</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col1\" class=\"data row4 col1\" >0.900449</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col2\" class=\"data row4 col2\" >0.002015</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.905012</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0.888060</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col5\" class=\"data row4 col5\" >0.897898</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0.909492</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.898676</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col8\" class=\"data row4 col8\" >0.914698</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col9\" class=\"data row4 col9\" >0.907273</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col10\" class=\"data row4 col10\" >0.887821</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col11\" class=\"data row4 col11\" >0.903462</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row4_col12\" class=\"data row4 col12\" >0.902174</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >3 <= text wordCnt < 10</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col0\" class=\"data row5 col0\" >0.749589</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0.737760</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0.011829</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.755394</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.732875</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col5\" class=\"data row5 col5\" >0.740514</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0.738432</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col7\" class=\"data row5 col7\" >0.748611</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col8\" class=\"data row5 col8\" >0.738828</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col9\" class=\"data row5 col9\" >0.751830</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col10\" class=\"data row5 col10\" >0.729560</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col11\" class=\"data row5 col11\" >0.751597</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row5_col12\" class=\"data row5 col12\" >0.749106</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >10 <= text wordCnt < 30</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col0\" class=\"data row6 col0\" >0.656765</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col1\" class=\"data row6 col1\" >0.631727</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col2\" class=\"data row6 col2\" >0.025038</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.662790</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.640966</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0.638470</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col6\" class=\"data row6 col6\" >0.611453</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col7\" class=\"data row6 col7\" >0.662320</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col8\" class=\"data row6 col8\" >0.634886</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col9\" class=\"data row6 col9\" >0.653764</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col10\" class=\"data row6 col10\" >0.627677</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col11\" class=\"data row6 col11\" >0.666482</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row6_col12\" class=\"data row6 col12\" >0.643655</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >30 <= text wordCnt < 100</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0.617644</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0.587510</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col2\" class=\"data row7 col2\" >0.030134</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.628807</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.638164</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col5\" class=\"data row7 col5\" >0.627505</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col6\" class=\"data row7 col6\" >0.479166</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0.614827</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col8\" class=\"data row7 col8\" >0.582364</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col9\" class=\"data row7 col9\" >0.615203</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col10\" class=\"data row7 col10\" >0.555669</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col11\" class=\"data row7 col11\" >0.601880</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row7_col12\" class=\"data row7 col12\" >0.682187</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row8\" class=\"row_heading level0 row8\" >0 <= selected text wordCnt < 3</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col0\" class=\"data row8 col0\" >0.533541</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col1\" class=\"data row8 col1\" >0.496990</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col2\" class=\"data row8 col2\" >0.036551</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col3\" class=\"data row8 col3\" >0.540171</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col4\" class=\"data row8 col4\" >0.496948</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col5\" class=\"data row8 col5\" >0.520520</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col6\" class=\"data row8 col6\" >0.488347</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col7\" class=\"data row8 col7\" >0.523077</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col8\" class=\"data row8 col8\" >0.482446</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col9\" class=\"data row8 col9\" >0.531564</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col10\" class=\"data row8 col10\" >0.487821</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col11\" class=\"data row8 col11\" >0.552373</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row8_col12\" class=\"data row8 col12\" >0.529385</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row9\" class=\"row_heading level0 row9\" >3 <= selected text wordCnt < 10</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col0\" class=\"data row9 col0\" >0.698831</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col1\" class=\"data row9 col1\" >0.681698</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col2\" class=\"data row9 col2\" >0.017133</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col3\" class=\"data row9 col3\" >0.703570</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col4\" class=\"data row9 col4\" >0.689631</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col5\" class=\"data row9 col5\" >0.681659</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col6\" class=\"data row9 col6\" >0.661955</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col7\" class=\"data row9 col7\" >0.712799</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col8\" class=\"data row9 col8\" >0.693418</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col9\" class=\"data row9 col9\" >0.699277</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col10\" class=\"data row9 col10\" >0.678731</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col11\" class=\"data row9 col11\" >0.696852</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row9_col12\" class=\"data row9 col12\" >0.684754</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row10\" class=\"row_heading level0 row10\" >10 <= selected text wordCnt < 30</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col0\" class=\"data row10 col0\" >0.881335</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col1\" class=\"data row10 col1\" >0.877453</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col2\" class=\"data row10 col2\" >0.003882</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col3\" class=\"data row10 col3\" >0.887725</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col4\" class=\"data row10 col4\" >0.882758</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col5\" class=\"data row10 col5\" >0.868845</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col6\" class=\"data row10 col6\" >0.863197</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col7\" class=\"data row10 col7\" >0.887144</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col8\" class=\"data row10 col8\" >0.887390</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col9\" class=\"data row10 col9\" >0.877808</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col10\" class=\"data row10 col10\" >0.879603</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col11\" class=\"data row10 col11\" >0.885152</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row10_col12\" class=\"data row10 col12\" >0.874315</td>\n","            </tr>\n","            <tr>\n","                        <th id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002level0_row11\" class=\"row_heading level0 row11\" >30 <= selected text wordCnt < 100</th>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col0\" class=\"data row11 col0\" >0.894234</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col1\" class=\"data row11 col1\" >0.889971</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col2\" class=\"data row11 col2\" >0.004262</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col3\" class=\"data row11 col3\" >0.907426</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col4\" class=\"data row11 col4\" >0.893070</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col5\" class=\"data row11 col5\" >0.891848</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col6\" class=\"data row11 col6\" >0.792278</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col7\" class=\"data row11 col7\" >0.904122</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col8\" class=\"data row11 col8\" >0.908788</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col9\" class=\"data row11 col9\" >0.892741</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col10\" class=\"data row11 col10\" >0.908811</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col11\" class=\"data row11 col11\" >0.875032</td>\n","                        <td id=\"T_2394a046_9d00_11ea_8965_0242ac1c0002row11_col12\" class=\"data row11 col12\" >0.946910</td>\n","            </tr>\n","    </tbody></table>"],"text/plain":["<pandas.io.formats.style.Styler at 0x7f5dc32c5198>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"yP3xG-Cenvry","colab_type":"text"},"source":["# Visualize predictions"]},{"cell_type":"code","metadata":{"_kg_hide-input":true,"id":"cGxcMVRMnvrz","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":704},"outputId":"0661fe0a-31cf-43f2-db2a-799747565a00","executionInfo":{"status":"ok","timestamp":1590243452089,"user_tz":180,"elapsed":6820782,"user":{"displayName":"Dimitre Oliveira","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjWI4QgYDUyC8ZcW5KHpuBwcY-MZWVqbPWcZSzxIg=s64","userId":"06256612867315483887"}}},"source":["display(k_fold[[c for c in k_fold.columns if not (c.startswith('textID') or \n","                                                  c.startswith('text_len') or \n","                                                  c.startswith('selected_text_len') or \n","                                                  c.startswith('text_wordCnt') or \n","                                                  c.startswith('selected_text_wordCnt') or \n","                                                  c.startswith('fold_') or \n","                                                  c.startswith('start_fold_') or \n","                                                  c.startswith('end_fold_'))]].head(15))"],"execution_count":18,"outputs":[{"output_type":"display_data","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>selected_text</th>\n","      <th>sentiment</th>\n","      <th>jaccard</th>\n","      <th>text_tokenCnt</th>\n","      <th>selected_text_tokenCnt</th>\n","      <th>prediction_fold_1</th>\n","      <th>jaccard_fold_1</th>\n","      <th>prediction_fold_2</th>\n","      <th>jaccard_fold_2</th>\n","      <th>prediction_fold_3</th>\n","      <th>jaccard_fold_3</th>\n","      <th>prediction_fold_4</th>\n","      <th>jaccard_fold_4</th>\n","      <th>prediction_fold_5</th>\n","      <th>jaccard_fold_5</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>i`d have responded, if i were going</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>10</td>\n","      <td>10</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>1.000000</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>1.000000</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>1.000000</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>1.000000</td>\n","      <td>i`d have responded, if i were going</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>sooo sad i will miss you here in san diego!!!</td>\n","      <td>sooo sad</td>\n","      <td>negative</td>\n","      <td>0.200000</td>\n","      <td>13</td>\n","      <td>3</td>\n","      <td>sad</td>\n","      <td>0.500000</td>\n","      <td>sad</td>\n","      <td>0.500000</td>\n","      <td>sad</td>\n","      <td>0.500000</td>\n","      <td>sad</td>\n","      <td>0.500000</td>\n","      <td>sad</td>\n","      <td>0.500000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>my boss is bullying me...</td>\n","      <td>bullying me</td>\n","      <td>negative</td>\n","      <td>0.166667</td>\n","      <td>6</td>\n","      <td>2</td>\n","      <td>bullying</td>\n","      <td>0.500000</td>\n","      <td>bullying me...</td>\n","      <td>0.333333</td>\n","      <td>my boss is bullying me...</td>\n","      <td>0.166667</td>\n","      <td>bullying me...</td>\n","      <td>0.333333</td>\n","      <td>bullying me...</td>\n","      <td>0.333333</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>what interview! leave me alone</td>\n","      <td>leave me alone</td>\n","      <td>negative</td>\n","      <td>0.600000</td>\n","      <td>6</td>\n","      <td>3</td>\n","      <td>what interview! leave me alone</td>\n","      <td>0.600000</td>\n","      <td>what interview! leave me alone</td>\n","      <td>0.600000</td>\n","      <td>what interview! leave me alone</td>\n","      <td>0.600000</td>\n","      <td>what interview! leave me alone</td>\n","      <td>0.600000</td>\n","      <td>what interview! leave me alone</td>\n","      <td>0.600000</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>sons of ****, why couldn`t they put them on th...</td>\n","      <td>sons of ****,</td>\n","      <td>negative</td>\n","      <td>0.214286</td>\n","      <td>17</td>\n","      <td>4</td>\n","      <td>sons of ****,</td>\n","      <td>1.000000</td>\n","      <td>sons of ****,</td>\n","      <td>1.000000</td>\n","      <td>sons of ****,</td>\n","      <td>1.000000</td>\n","      <td>sons of ****,</td>\n","      <td>1.000000</td>\n","      <td>sons of ****,</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>27</td>\n","      <td>27</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>1.000000</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>1.000000</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>1.000000</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>1.000000</td>\n","      <td>http://www.dothebouncy.com/smf - some shameles...</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>2am feedings for the baby are fun when he is a...</td>\n","      <td>fun</td>\n","      <td>positive</td>\n","      <td>0.071429</td>\n","      <td>17</td>\n","      <td>1</td>\n","      <td>fun</td>\n","      <td>1.000000</td>\n","      <td>fun</td>\n","      <td>1.000000</td>\n","      <td>fun</td>\n","      <td>1.000000</td>\n","      <td>fun</td>\n","      <td>1.000000</td>\n","      <td>fun</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>soooo high</td>\n","      <td>soooo high</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>soooo high</td>\n","      <td>1.000000</td>\n","      <td>soooo high</td>\n","      <td>1.000000</td>\n","      <td>soooo high</td>\n","      <td>1.000000</td>\n","      <td>soooo high</td>\n","      <td>1.000000</td>\n","      <td>soooo high</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>both of you</td>\n","      <td>both of you</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>both of you</td>\n","      <td>1.000000</td>\n","      <td>both of you</td>\n","      <td>1.000000</td>\n","      <td>both of you</td>\n","      <td>1.000000</td>\n","      <td>both of you</td>\n","      <td>1.000000</td>\n","      <td>both of you</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>journey!? wow... u just became cooler.  hehe.....</td>\n","      <td>wow... u just became cooler.</td>\n","      <td>positive</td>\n","      <td>0.500000</td>\n","      <td>19</td>\n","      <td>7</td>\n","      <td>wow... u just became cooler.</td>\n","      <td>1.000000</td>\n","      <td>journey!? wow... u just became cooler.</td>\n","      <td>0.833333</td>\n","      <td>journey!? wow... u just became cooler.</td>\n","      <td>0.833333</td>\n","      <td>wow...</td>\n","      <td>0.200000</td>\n","      <td>wow... u just became cooler.</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>27</td>\n","      <td>27</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>1.000000</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>1.000000</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>1.000000</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>1.000000</td>\n","      <td>as much as i love to be hopeful, i reckon the ...</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>i really really like the song love story by ta...</td>\n","      <td>like</td>\n","      <td>positive</td>\n","      <td>0.100000</td>\n","      <td>12</td>\n","      <td>1</td>\n","      <td>like</td>\n","      <td>1.000000</td>\n","      <td>i really really like</td>\n","      <td>0.333333</td>\n","      <td>like</td>\n","      <td>1.000000</td>\n","      <td>i really really like</td>\n","      <td>0.333333</td>\n","      <td>like</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>my sharpie is running dangerously low on ink</td>\n","      <td>dangerously</td>\n","      <td>negative</td>\n","      <td>0.125000</td>\n","      <td>9</td>\n","      <td>1</td>\n","      <td>dangerously low on ink</td>\n","      <td>0.250000</td>\n","      <td>dangerously low on ink</td>\n","      <td>0.250000</td>\n","      <td>dangerously low on ink</td>\n","      <td>0.250000</td>\n","      <td>dangerously low on ink</td>\n","      <td>0.250000</td>\n","      <td>my sharpie is running dangerously low on ink</td>\n","      <td>0.125000</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>i want to go to music tonight but i lost my vo...</td>\n","      <td>lost</td>\n","      <td>negative</td>\n","      <td>0.100000</td>\n","      <td>13</td>\n","      <td>1</td>\n","      <td>lost my voice.</td>\n","      <td>0.333333</td>\n","      <td>lost my voice.</td>\n","      <td>0.333333</td>\n","      <td>lost my voice.</td>\n","      <td>0.333333</td>\n","      <td>lost my voice.</td>\n","      <td>0.333333</td>\n","      <td>lost my voice.</td>\n","      <td>0.333333</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>test test from the lg env2</td>\n","      <td>test test from the lg env2</td>\n","      <td>neutral</td>\n","      <td>1.000000</td>\n","      <td>8</td>\n","      <td>8</td>\n","      <td>test test from the lg env2</td>\n","      <td>1.000000</td>\n","      <td>test test from the lg env2</td>\n","      <td>1.000000</td>\n","      <td>test test from the lg env2</td>\n","      <td>1.000000</td>\n","      <td>test test from the lg env2</td>\n","      <td>1.000000</td>\n","      <td>test test from the lg env2</td>\n","      <td>1.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                                                 text  ... jaccard_fold_5\n","0                 i`d have responded, if i were going  ...       1.000000\n","1       sooo sad i will miss you here in san diego!!!  ...       0.500000\n","2                           my boss is bullying me...  ...       0.333333\n","3                      what interview! leave me alone  ...       0.600000\n","4   sons of ****, why couldn`t they put them on th...  ...       1.000000\n","5   http://www.dothebouncy.com/smf - some shameles...  ...       1.000000\n","6   2am feedings for the baby are fun when he is a...  ...       1.000000\n","7                                          soooo high  ...       1.000000\n","8                                         both of you  ...       1.000000\n","9   journey!? wow... u just became cooler.  hehe.....  ...       1.000000\n","10  as much as i love to be hopeful, i reckon the ...  ...       1.000000\n","11  i really really like the song love story by ta...  ...       1.000000\n","12       my sharpie is running dangerously low on ink  ...       0.125000\n","13  i want to go to music tonight but i lost my vo...  ...       0.333333\n","14                         test test from the lg env2  ...       1.000000\n","\n","[15 rows x 16 columns]"]},"metadata":{"tags":[]}}]}]}