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Available only ...\n", + "1 ham Ok lar... Joking wif u oni...\n", + "2 spam Free entry in 2 a wkly comp to win FA Cup fina...\n", + "3 ham U dun say so early hor... U c already then say...\n", + "4 ham Nah I don't think he goes to usf, he lives aro..." + ], + "text/html": [ + "\n", + "
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Available only in bugis n great world la e buffet... Cine there got amore wat...',\n", + " 'Ok lar... Joking wif u oni...',\n", + " \"Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive entry question(std txt rate)T&C's apply 08452810075over18's\",\n", + " 'U dun say so early hor... U c already then say...',\n", + " \"Nah I don't think he goes to usf, he lives around here though\"]" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ] + }, + { + "cell_type": "code", + "source": [ + "y[:5]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "tynaJaplX8rv", + "outputId": "7f8870c2-71b9-4fa8-b733-d0524e2b5e51" + }, + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['ham', 'ham', 'spam', 'ham', 'ham']" + ] + }, + "metadata": {}, + "execution_count": 6 + } + ] + }, + { + "cell_type": "code", + "source": [ + "y = list(pd.get_dummies(y)['spam'])\n", + "y[:5]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "GcgVpVO3X-N4", + "outputId": "ab3a68c7-dd95-4b48-bc72-fd80ab0128d4" + }, + "execution_count": 7, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "[0, 0, 1, 0, 0]" + ] + }, + "metadata": {}, + "execution_count": 7 + } + ] + }, + { + "cell_type": "code", + "source": [ + "x_train , x_test , y_train , y_test = train_test_split(x , y ,test_size = 0.2 , random_state=0)" + ], + "metadata": { + "id": "Y595det5Yhak" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "len(x_train)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "0snMxb5nZIqX", + "outputId": "37a3ffaa-8a1a-4d86-f963-568167651b67" + }, + "execution_count": 9, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "4457" + ] + }, + "metadata": {}, + "execution_count": 9 + } + ] + }, + { + "cell_type": "code", + "source": [ + "len(x_test)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Jrq5fmh6ZM_J", + "outputId": "89f0c95c-e78c-4986-f682-154ed6dff89b" + }, + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1115" + ] + }, + "metadata": {}, + "execution_count": 10 + } + ] + }, + { + "cell_type": "code", + "source": [ + "from transformers import DistilBertTokenizerFast\n", + "tokenizer = DistilBertTokenizerFast.from_pretrained('distilbert-base-uncased')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 145, + "referenced_widgets": [ + "1d6a3b0c00234ec8a2ca42e0fcacae12", + "c07afe1743d24f569434f50c3a6cbbdb", + "e5c8acc65cfb447da17da6318aed2627", + "33daf3fbb1a74324ad1240c756c048f7", + "3ed265430c694921aa3e612fc1f3fde7", + "5256eb24407c4dcc8219dec4a03393df", + "9a5feca3976c461a8c98be3e60553534", + "c5e96ab5e41048ce96e8ec73a2a96d94", + "67777ce4e577461194f178ba1bd826cd", + "2f725e866fa744fbbba18c1edbb1ef82", + "2bf78f4e4f3542c1ab65366541e795ad", + "a03619774dc24edaaa87a2680ad21c59", + "1dc893a61b9040f1b2ddd188c0aba8de", + "8d7bdb534cf648f081c63f3a965efb62", + "810ec1c041204ffbbec8e4499ae75592", + "27eb24ed7741413b8d9e9ff928d3931b", + "14404a66da234fcaa9cd6b63177aecc9", + "23d6b99080a44b6db5b935498d5c91e0", + "3126b0ca3d3b43b0a4e39b2bd9dc7fe4", + "c135e626829c4e5b9a4b79316ede1b56", + "acb55f6c155e4a5ba587c26227ef26d5", + "6fc86754d792468eb39c33802f8af2a6", + "c2012f0e8909444fb9b0417645caa361", + "dc558ae7d5644e06b6bcbdf3ea3544e7", + "ef174000b8234fe68ab3b7ddd2692000", + "d71783a5e2d94181a56b44d7fb566d52", + "2b15f5090bf8499787b692de53a231a7", + "b74f6f4772a74d029a316828dc90d638", + "3e1cc0c559684c58a36f53ecf9a19884", + "61a3f519bbe54648a51fb8bb3fedf26f", + "5c100a992b814383903189c698c18e39", + "df0cb05b229d4646ba696027ff979ee5", + "71ce09c004fb4292a99d34dd3c5ee779", + "711af41870d04057b62081f48d4afb1e", + "796c75d5ba314c0f8083e7ff24c1a5a0", + "40fa6cd37b014f77ba0f4f7886754baf", + "404601953f304464b925d1c9d497cbf1", + "4863938828e54f7e95b76b4409033693", + "d3616414bcbe4080a324fa59d7be335e", + "bf3755bb0f96434a9756699568784681", + "e1e01409379544b6b0c63e21dd9680bb", + "1bf28dcf6b234e16b9d247eb985b7f01", + "428e73a1d1bf4cfa97e2c72768f68323", + "a375c9e83d4b47d08a0dfa551d32f0f7" + ] + }, + "id": "j1rKS8vGZUlT", + "outputId": "dff61afb-db58-40b2-aee2-15814bcd47cc" + }, + "execution_count": 11, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "tokenizer_config.json: 0%| | 0.00/28.0 [00:00" + ] + }, + "metadata": {}, + "execution_count": 15 + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "from transformers import TFDistilBertForSequenceClassification , TFTrainer , TFTrainingArguments\n", + "\n", + "training_args = TFTrainingArguments(\n", + " output_dir = './results',\n", + " num_train_epochs = 2,\n", + " per_device_train_batch_size = 8,\n", + " per_device_eval_batch_size = 16,\n", + " eval_steps=100,\n", + " warmup_steps = 500,\n", + " weight_decay = 0.01,\n", + " logging_dir = './logs',\n", + " logging_steps = 10,\n", + ")" + ], + "metadata": { + "id": "pH-kNycicDPY" + }, + "execution_count": 16, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "\n", + "with training_args.strategy.scope():\n", + " model = TFDistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased',id2label=id2label, label2id=label2id)\n", + "\n", + "trainer = TFTrainer(\n", + " model = model,\n", + " args = training_args,\n", + " train_dataset = train_dataset,\n", + " eval_dataset = test_dataset\n", + ")\n", + "\n", + "model.config.use_cache = False\n", + "trainer.train()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 190, + "referenced_widgets": [ + "d3607926ad3344bfa3733c5aada91527", + "4836025b3bd44e07ad6562d4f5982980", + "c267e99678c94fa489f06e1bb89b4a01", + "ea6499ba78304663909476952f1405b3", + "c8e8a5e063b343e6bef3372c778674e3", + "d6be679cb8f94ab9ba865d949a247115", + "520562eae87649d49634677d581f8c55", + "c1bc256f2571428b882373c2533fa965", + "1719ebad8bbb47ee89e4683f57eb8c6d", + "fda4bf2faf114cf2aaf51d6f22dd9c2b", + "5f30d7d3cd374eb4b277be0a805c2074" + ] + }, + "id": "kxRiLtfmdXjR", + "outputId": "4ecd0769-a0c0-43bf-ea1d-3f0323a16634" + }, + "execution_count": 17, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "model.safetensors: 0%| | 0.00/268M [00:00