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+ " category text\n",
+ "0 Technical writer organize material and complete writing assignm...\n",
+ "1 Technical writer maintain records and files of work and revisions\n",
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+ "id": "4dp6V2sc-Yy0",
+ "outputId": "3801fb3f-3e7a-482c-9798-2026a6c96cf3"
+ },
+ "execution_count": 26,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ " category text \\\n",
+ "0 Technical writer organize material and complete writing assignm... \n",
+ "1 Technical writer maintain records and files of work and revisions \n",
+ "2 Technical writer edit standardize or make changes to material... \n",
+ "3 Technical writer select photographs drawings sketches diagra... \n",
+ "4 Technical writer interview production and engineering personnel... \n",
+ "\n",
+ " encoded_cat \n",
+ "0 55 \n",
+ "1 55 \n",
+ "2 55 \n",
+ "3 55 \n",
+ "4 55 "
+ ],
+ "text/html": [
+ "\n",
+ " \n",
+ "
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+ "
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+ "\n",
+ "
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+ " \n",
+ " \n",
+ " \n",
+ " category \n",
+ " text \n",
+ " encoded_cat \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 \n",
+ " Technical writer \n",
+ " organize material and complete writing assignm... \n",
+ " 55 \n",
+ " \n",
+ " \n",
+ " 1 \n",
+ " Technical writer \n",
+ " maintain records and files of work and revisions \n",
+ " 55 \n",
+ " \n",
+ " \n",
+ " 2 \n",
+ " Technical writer \n",
+ " edit standardize or make changes to material... \n",
+ " 55 \n",
+ " \n",
+ " \n",
+ " 3 \n",
+ " Technical writer \n",
+ " select photographs drawings sketches diagra... \n",
+ " 55 \n",
+ " \n",
+ " \n",
+ " 4 \n",
+ " Technical writer \n",
+ " interview production and engineering personnel... \n",
+ " 55 \n",
+ " \n",
+ " \n",
+ "
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+ "
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+ "
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+ " \n",
+ " \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ "\n",
+ " \n",
+ "
\n",
+ "
\n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "execution_count": 26
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "data_texts = df[\"text\"].to_list() # Features (not-tokenized yet)\n",
+ "data_labels = df[\"encoded_cat\"].to_list() # Lables"
+ ],
+ "metadata": {
+ "id": "nwha3xMv-bWE"
+ },
+ "execution_count": 5,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from sklearn.model_selection import train_test_split\n",
+ "\n",
+ "# Split Train and Validation data\n",
+ "train_texts, val_texts, train_labels, val_labels = train_test_split(data_texts, data_labels, test_size=0.2, random_state=1000)"
+ ],
+ "metadata": {
+ "id": "V0L894Ah-f4Y"
+ },
+ "execution_count": 6,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')\n",
+ "train_encodings = tokenizer(train_texts, truncation=True, padding=True)\n",
+ "val_encodings = tokenizer(val_texts, truncation=True, padding=True)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 113,
+ "referenced_widgets": [
+ "461e999f2baa48dc9358d0c2e2359ac2",
+ "ab805ac6f2b24958b586a8a36f61f672",
+ "91ed8056b9b94003aee11323abed8bac",
+ "f240e2d7570a4e349282f196d9736b58",
+ "98ac0a81526942408bd5b1ccfac8ff26",
+ "2f346d4b383b47959436e36defb3fe75",
+ "55fbc0a36d8644faa67a3b50b33b4c35",
+ "2e780239f4bf4092806cf39cc1c406bc",
+ "3b36ca1930444e07a0c2f18ee3cf9ef5",
+ "5e223ce013604e81af0bc3e3c79fd910",
+ "5bdced15d97c4c7986dba43e63c469d4",
+ "fe87ef54ccd641399374545aff94f259",
+ "17c29f73f13146c8a9757388036bd75f",
+ "8f009cfff19741f993d4053d8c7e2550",
+ "1b4a2d5e7c45484d95f2f471f81f9268",
+ "34437e4f680846028c5cf25bcd937e31",
+ "5e9cda6f2c264bbe99253757aac958a3",
+ "9f1e341d8be04d49bd97d22015647668",
+ "047961164e0c46bc8bee0fdaee0855b9",
+ "6b434e98fee64e13a270fd112e729fe4",
+ "c98381ad02a54131b69bc6914bd83f28",
+ "d20ee5b9ae254dea916b658e9a8d59fc",
+ "5a7ddb670889497390a5657842580fa9",
+ "5a7e101b97f04ba59e074da08cd39825",
+ "eccdafb2f76240f78658e8f8c880ab49",
+ "5d8d81d726c8463fa6a6c9caa645a168",
+ "37f2d7bb5b534b7982b3d05af333dbfe",
+ "788e946000e94525968a02c7b2ae9a36",
+ "e1476a728863456994a890d831222bd8",
+ "eab87aeb74aa4c24bcc9a670b9730679",
+ "88146e2449b142e19f1fef687753ab28",
+ "4e98bfe17ed049448426b43a12fbf1af",
+ "ab984301e30a4d9589512feee5496177"
+ ]
+ },
+ "id": "b44iBVaZ-jV0",
+ "outputId": "9f315315-19e3-4f18-a556-2df4d2210fdf"
+ },
+ "execution_count": 7,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading (…)solve/main/vocab.txt: 0%| | 0.00/232k [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "461e999f2baa48dc9358d0c2e2359ac2"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading (…)okenizer_config.json: 0%| | 0.00/28.0 [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "fe87ef54ccd641399374545aff94f259"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading (…)lve/main/config.json: 0%| | 0.00/483 [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "5a7ddb670889497390a5657842580fa9"
+ }
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "train_dataset = tf.data.Dataset.from_tensor_slices((\n",
+ " dict(train_encodings),\n",
+ " train_labels\n",
+ "))\n",
+ "val_dataset = tf.data.Dataset.from_tensor_slices((dict(val_encodings), val_labels ))"
+ ],
+ "metadata": {
+ "id": "QNzTP8Oc-m2_"
+ },
+ "execution_count": 8,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "model = TFDistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased', num_labels=21)\n",
+ "\n",
+ "optimizer = tf.keras.optimizers.Adam(learning_rate=5e-5)\n",
+ "model.compile(optimizer=optimizer, loss=model.compute_loss, metrics=['accuracy'])"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 156,
+ "referenced_widgets": [
+ "4a5d41d73777496786e7ca27eff555a8",
+ "f38c76b6a69e4732be4096d8a5f06cff",
+ "3dfcd9c4b5b04157b5f8ca5d95e2248b",
+ "e613da760f9748748f3ef4d0a6ad028c",
+ "48587a90cfe843d7a167c050eb5c9c8c",
+ "b4c9d4bd610f4ae0ae6961103c6d1e4b",
+ "27ea011de69a493896b1544d5be73fe8",
+ "b5a297f49741447e92bb7ef60aa535ac",
+ "d3086c0521fb4c4d9c91e6c933eec4d4",
+ "5210dac42ffc4634b375736d8c6d082f",
+ "ff0c57a0e7bd40a7bb23f4471ad45273"
+ ]
+ },
+ "id": "sk1VjA2Y-pZr",
+ "outputId": "b30789c4-eb6a-413e-d8af-66641c43bdb4"
+ },
+ "execution_count": 9,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Downloading tf_model.h5: 0%| | 0.00/363M [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "4a5d41d73777496786e7ca27eff555a8"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "Some layers from the model checkpoint at distilbert-base-uncased were not used when initializing TFDistilBertForSequenceClassification: ['vocab_transform', 'activation_13', 'vocab_projector', 'vocab_layer_norm']\n",
+ "- This IS expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+ "- This IS NOT expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
+ "Some layers of TFDistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['dropout_19', 'pre_classifier', 'classifier']\n",
+ "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "model.fit(train_dataset.shuffle(100).batch(16), epochs=5, batch_size=16, validation_data=val_dataset.shuffle(100).batch(16))"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "q8fjF_A1-sP2",
+ "outputId": "fe931082-28db-4a23-c470-3a237545219e"
+ },
+ "execution_count": 11,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Epoch 1/5\n",
+ "62/62 [==============================] - 8s 123ms/step - loss: 1.5237 - accuracy: 0.5237 - val_loss: 2.2847 - val_accuracy: 0.3024\n",
+ "Epoch 2/5\n",
+ "62/62 [==============================] - 7s 105ms/step - loss: 1.4421 - accuracy: 0.5378 - val_loss: 2.3720 - val_accuracy: 0.2823\n",
+ "Epoch 3/5\n",
+ "62/62 [==============================] - 7s 106ms/step - loss: 1.3973 - accuracy: 0.5439 - val_loss: 2.4879 - val_accuracy: 0.2742\n",
+ "Epoch 4/5\n",
+ "62/62 [==============================] - 7s 105ms/step - loss: 1.3523 - accuracy: 0.5610 - val_loss: 2.4525 - val_accuracy: 0.2944\n",
+ "Epoch 5/5\n",
+ "62/62 [==============================] - 7s 111ms/step - loss: 1.3322 - accuracy: 0.5469 - val_loss: 2.5269 - val_accuracy: 0.2944\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "execution_count": 11
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "save_directory = \"/saved_models\" # change this to your preferred location\n",
+ "\n",
+ "model.save_pretrained(save_directory)\n",
+ "tokenizer.save_pretrained(save_directory)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "QOgRMyjz_cdb",
+ "outputId": "f41136b6-5abb-43ed-c414-b3df98013ce2"
+ },
+ "execution_count": 12,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "('/saved_models/tokenizer_config.json',\n",
+ " '/saved_models/special_tokens_map.json',\n",
+ " '/saved_models/vocab.txt',\n",
+ " '/saved_models/added_tokens.json')"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 12
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "loaded_tokenizer = DistilBertTokenizer.from_pretrained(save_directory)\n",
+ "loaded_model = TFDistilBertForSequenceClassification.from_pretrained(save_directory)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "5FoDCmk1_-MO",
+ "outputId": "983d5b90-1c81-46e4-a113-7d63dbadb4f6"
+ },
+ "execution_count": 13,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "Some layers from the model checkpoint at /saved_models were not used when initializing TFDistilBertForSequenceClassification: ['dropout_19']\n",
+ "- This IS expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+ "- This IS NOT expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
+ "Some layers of TFDistilBertForSequenceClassification were not initialized from the model checkpoint at /saved_models and are newly initialized: ['dropout_39']\n",
+ "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip install huggingface_hub"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "-YpirwFG5IIR",
+ "outputId": "0172d5d2-34f1-4c00-9d46-81c4709bef74"
+ },
+ "execution_count": 17,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.9/dist-packages (0.13.3)\n",
+ "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (6.0)\n",
+ "Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (2.27.1)\n",
+ "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (23.0)\n",
+ "Requirement already satisfied: filelock in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (3.10.7)\n",
+ "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (4.65.0)\n",
+ "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from huggingface_hub) (3.7.4.3)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface_hub) (2022.12.7)\n",
+ "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface_hub) (2.0.12)\n",
+ "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface_hub) (1.26.15)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->huggingface_hub) (3.4)\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "\n",
+ "from huggingface_hub import notebook_login\n",
+ "\n",
+ "notebook_login()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 387,
+ "referenced_widgets": [
+ "7aa5bc080dad4be6b0ac49fe0240ce89",
+ "715119cd9a58493db5983d62d9d8bad5",
+ "e350eee1c20348e598ca3707ebe2068b",
+ "1ca3d1be0d464ca0a25c678c540d2cb4",
+ "c37d1ccf56fc431e99924a9a978ec2ef",
+ "50b3c2e37a0a430e9384316777a66abe",
+ "b10679fb7d9f4ddbaf5638d8ee3caaa3",
+ "dc47e25dfbcb406cae40caed3340d2cb",
+ "8b706e4a73f8444b9242ffd9a6d51dcd",
+ "74251c2768b5449dbc94a75ab2a4f20c",
+ "a89885231e0e4df994a051fd07dd1b55",
+ "c1ab0ff13c0f4c0b89b9c76c6fb7f661",
+ "1cf5fd8e9b3a423bafc47e9fd5ec4fb8",
+ "220ec08abd764f8c8b960f316fb653ed",
+ "158d2eda521547f89bc645f34d9de3de",
+ "4b4098c342c74ba08f6330313a0f1022",
+ "08d9cc833707450d8743e49d8ac0dacf"
+ ]
+ },
+ "id": "0_vOrKPy5VMX",
+ "outputId": "cbe9c75d-14a9-49b1-c803-91f18d81321c"
+ },
+ "execution_count": 18,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Token is valid.\n",
+ "Your token has been saved in your configured git credential helpers (store).\n",
+ "Your token has been saved to /root/.cache/huggingface/token\n",
+ "Login successful\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "model.push_to_hub(\"lfernandopg/Proyecto-Transformers\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 81,
+ "referenced_widgets": [
+ "7baac729da904ceeacfdc3e87b524d66",
+ "526d7f9597b844d399f48013d1c25471",
+ "6392c9c107554f6da5329d647bf55656",
+ "548acdc1bce6487a80e249dedb8a3064",
+ "fb6e997a32f7459e995ffac7624af8a5",
+ "9fa787762c594275ba9664b757618323",
+ "493aac2bf5c340b9ac8ca3be2b39479f",
+ "a8a7b0d2f00c4a04a12dcac14353bcd0",
+ "c0d25439b2dc49788a9cd0967ef7e41e",
+ "36e83b61ae7445a9b5a1dd91ecfc2f1a",
+ "9bb6745fa7484698bf5e342bc75d7960",
+ "16c3c53007eb4397a177bb9916e92359",
+ "66f1907c4b064d40887540d2a6e82e7f",
+ "09c59356ac5f438888e9693e5da5c27e",
+ "23cb49268ac849668fd66e1cbd7839b4",
+ "3f8b3354f3154c0180e01c9ebf2d4d03",
+ "cede094415ac4c6c9226d4c244eba2ea",
+ "6b175a405eeb4d9b9e0966c47d98d00e",
+ "bd57483e4b254d038aef9d6acaf5c8e6",
+ "6a7372d350ae45dd8f5844caf81c1590",
+ "b69898022c7a485caf578ba7100ff658",
+ "2f19e4fa46834e38a47153d8143f8cfd"
+ ]
+ },
+ "id": "itffU8Ke6ET5",
+ "outputId": "f3d96331-8117-475e-fbd6-e2aa5bee5f06"
+ },
+ "execution_count": 20,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "tf_model.h5: 0%| | 0.00/268M [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "7baac729da904ceeacfdc3e87b524d66"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "Upload 1 LFS files: 0%| | 0/1 [00:00, ?it/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "16c3c53007eb4397a177bb9916e92359"
+ }
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "tokenizer.push_to_hub(\"lfernandopg/Proyecto-Transformers\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "q2RzBT9lFobI",
+ "outputId": "01a9590a-0659-4556-b79b-00b42a3f873c"
+ },
+ "execution_count": 24,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "CommitInfo(commit_url='https://huggingface.co/lfernandopg/Proyecto-Transformers/commit/609ec9a9f028cf40873cd1180aa1776bdb0126b9', commit_message='Upload tokenizer', commit_description='', oid='609ec9a9f028cf40873cd1180aa1776bdb0126b9', pr_url=None, pr_revision=None, pr_num=None)"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 24
+ }
+ ]
+ }
+ ]
+}
\ No newline at end of file