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"model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } }, "gpuClass": "standard" }, "cells": [ { "cell_type": "code", "metadata": { "id": "09dbxhoYwOqr", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c60e6137-301c-4735-b72d-f0b2b8607cdf" }, "source": [ "!nvidia-smi" ], "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mon Aug 15 18:34:16 2022 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\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", "| | | MIG M. |\n", "|===============================+======================+======================|\n", "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 60C P8 13W / 70W | 0MiB / 15109MiB | 0% Default |\n", "| | | N/A |\n", "+-------------------------------+----------------------+----------------------+\n", " \n", "+-----------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=============================================================================|\n", "| No running processes found |\n", "+-----------------------------------------------------------------------------+\n" ] } ] }, { "cell_type": "code", "metadata": { "id": "MOsHUjgdIrIW", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c679e312-4072-4961-818c-787bf597180e" }, "source": [ "! pip install datasets transformers rouge-score nltk py7zr\n", "! pip install wandb -qq" ], "execution_count": 2, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting datasets\n", " Downloading datasets-2.4.0-py3-none-any.whl (365 kB)\n", "\u001b[K |████████████████████████████████| 365 kB 4.7 MB/s \n", "\u001b[?25hCollecting transformers\n", " Downloading transformers-4.21.1-py3-none-any.whl (4.7 MB)\n", "\u001b[K |████████████████████████████████| 4.7 MB 68.3 MB/s \n", "\u001b[?25hCollecting rouge-score\n", " Downloading rouge_score-0.1.2.tar.gz (17 kB)\n", "Requirement already satisfied: nltk in /usr/local/lib/python3.7/dist-packages (3.7)\n", "Collecting py7zr\n", " Downloading py7zr-0.20.0-py3-none-any.whl (64 kB)\n", "\u001b[K |████████████████████████████████| 64 kB 3.9 MB/s \n", "\u001b[?25hRequirement already satisfied: importlib-metadata in 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"\u001b[?25h Building wheel for pathtools (setup.py) ... \u001b[?25l\u001b[?25hdone\n" ] } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 121 }, "id": "hz2aNVWrSrBs", "outputId": "35a46922-4608-402a-b1f4-a40405cc59a1" }, "source": [ "import wandb\n", "wandb.login()" ], "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "application/javascript": [ "\n", " window._wandbApiKey = new Promise((resolve, reject) => {\n", " function loadScript(url) {\n", " return new Promise(function(resolve, reject) {\n", " let newScript = document.createElement(\"script\");\n", " newScript.onerror = reject;\n", " newScript.onload = resolve;\n", " document.body.appendChild(newScript);\n", " newScript.src = url;\n", " });\n", " }\n", " loadScript(\"https://cdn.jsdelivr.net/npm/postmate/build/postmate.min.js\").then(() => {\n", " const iframe = document.createElement('iframe')\n", " iframe.style.cssText = \"width:0;height:0;border:none\"\n", " document.body.appendChild(iframe)\n", " const handshake = new Postmate({\n", " container: iframe,\n", " url: 'https://wandb.ai/authorize'\n", " });\n", " const timeout = setTimeout(() => reject(\"Couldn't auto authenticate\"), 5000)\n", " handshake.then(function(child) {\n", " child.on('authorize', data => {\n", " clearTimeout(timeout)\n", " resolve(data)\n", " });\n", " });\n", " })\n", " });\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mwandb\u001b[0m: Logging into wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n", "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n", "wandb: Paste an API key from your profile and hit enter, or press ctrl+c to quit: " ] }, { "name": "stdout", "output_type": "stream", "text": [ "··········\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "True" ] }, "metadata": {}, "execution_count": 3 } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0ox1jdfIS1os", "outputId": "a828c506-aa84-4e25-d082-022f2eb9a407" }, "source": [ "%env WANDB_PROJECT=bart_large_xsum_samsum" ], "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "env: WANDB_PROJECT=bart_large_xsum_samsum\n" ] } ] }, { "cell_type": "code", "metadata": { "id": "TkXftRLYwOqc" }, "source": [ "model_checkpoint = \"facebook/bart-large-xsum\"" ], "execution_count": 5, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "whPRbBNbIrIl" }, "source": [ "## Loading the dataset" ] }, { "cell_type": "code", "metadata": { "id": "IreSlFmlIrIm", "colab": { "base_uri": "https://localhost:8080/", "height": 232, "referenced_widgets": [ "c013f31331f4414ba93296bc6eac6bd0", "3bafae27fc6c4931aed19e963435a4ba", "a2b3f6d9ae344e618d25d1d7d3de5a08", "e15c2ad3577d4898b5182a0414f45e1b", "fbcbd783aa8b47bdba1fab383be8c363", "940e8bc86eb149c781b4fde5f26f08aa", "b2d5c54b24c24965bc3f5a4efbbaf22e", "bccd010d2594413781acd14615273fbc", "e7f74e5a7b304caca8c4b8bf8f68a9bc", "d22385a67e6848cba5ab073818de74ac", "fb49829d79904d7e9ca71bfb755a88e2", "18c3df098f274421af4fb1d5849be016", "e34a07ce4a1143e2be55679510b24656", "ee99b40829d94fea88b80b3532b1c143", "d56aa431bb0a4097b8162dcec057d606", "1066703f861c47059df199330b8f1673", "4acc3d649daf4884b697581a90e98227", "dbb951325da94142ba0143c23636d87f", "ec9447facef643fb899e35e8418fa5e8", "f5ec6f4171a840ea8fd6a724ec088201", "8b38612e0bfe4521b17cc19295e9cc37", "332ec11fde01482087f7c5996c286665", "10b7cc876edf4c318e52a1a52155436b", "8326068728ea4c0d93d2470715f282bf", "865a6717333a4f91afd4a89c6d9c6af3", "3b7140665fd44b889fc3da085f712fec", "289f1d2550b14a91812ce318c2c3c57e", "6bea7e08adb64450bcb19389963d4b5d", "384959b7cd514848b61030bce4c359d6", "1495be8bb1724136b1d27514139cca9f", "a69d21a1118643f69b5ad65d14aff9b5", "f20a4edf1b7744b1aecf1fdfeef202cb", "ed5f5146face4d34bf2ce79e016486c6", "1576a0d55e4b42d49b9c981c3eb5226a", "50a96704909f44f28b2876977c52018b", "806be648f3064a45877d41abe130fea3", "e6532fdb85da49e0a01e40d8e0748de9", "784b1d177731419099d8d111303f48ac", "6fc406480d7744d4af92a003360c0ca3", "cd862011a74f4cf19e46492d244425b5", "0c8be3242e574f6c8c033b067595bc01", "9f58e4988df24e15a0808b3ce8beb83a", "ce3590e5ddfc4891ad2d306583aca20f", "c499cae2109440f49cb7b5ec33feb249", "869bd6be749d441bac77d2349d4b8b58", "390f1b745b4a431ebe650a8b4a4f4f3c", "0eed8b5fad77496fbd6594a3abb1676b", "5e143a4c08ee4011be22429887461309", "80b1b9f8292d4566b6dca8ee702491f9", "8ceebafb285e4a57a3c597c23042c39f", "fa79702f34414cbda0d99015ac2ac5ed", "75c483365dfd4d71819fb56d2027ccf2", "bb4d181db0d64ffc9464030278747de7", "9c55fcec95564aadb2d0efc458d73952", "7a8e91969d5445f4b3c4075492b9a5de", "24da9cb7a7e74c7cb74f04e4bb131f38", "7dfd43af3f674d618c57809f87f88d7b", "bd13176d197046ba8ca9bc762343587e", "10e3b675cd1e4805a9422b7a04a8698f", "5dc729150dca42e19de40bdb931e8ed3", "bb7fe17e063f4a599f13d4534ff8b85c", "ce27dcaa1c76404e9f4b62c02c3f5175", "6642038894564bcb8e055d0bc00e8281", "42fa5efab577451db9e4a4a79a399c09", "bc2a4b5fbcf74a46a3e27b267df27f56", "b57bf54670ca4df29144df666d14c17d", "189182420928480798e08944f0312ebd", "bb9f1b2c90404d5ba681e0b1bd3257ad", "babefc6104e74c8e8108146f68c71cee", "d1be2b9128c04aa9811c307076296f0e", "2be2c8ddaadf450eaf72582ac0ed9da9", "7b47ccc3fe3149b2858ab5d3e899f5e9", "c514d9798ef04202a945157a07882e12", "da6edee24b7d4bb2824fe34585080113", "e79ac5157ab14481aeabc05126dfb77a", "6459df288f1940f8bdba46af97f2b807", "a82d3f4b43234773b60717f929a015de", "e2710807269a44af9b77cdc43b294e6f", "0470e3033ae34f7c82ea419428264b8b", "d1388d6a0df643dda5fd7872dd30d08f", "d461c348134e4350b2aa53486745db28", "15d716ba9f1241d48c5ebe364e9aebcf", "2bf1794ecc7642348c7a5d13c3fb54ca", "0c6ab7605f38491d85fe24dacf834e1d", "66a06ae2221d4c6d81f7d05e91f292ba", "3d432e5ce8cf44d888188f15726334b0", "d3c98f7840314ddb94a4f23ec601748c", "26023e45046d4873982d1baa703492ff" ] }, "outputId": "68e6e715-ec35-442c-cca4-ff005c0df57e" }, "source": [ "from datasets import load_dataset, load_metric\n", "\n", "raw_datasets = load_dataset(\"samsum\")\n", "metric = load_metric(\"rouge\")" ], "execution_count": 6, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/1.40k [00:00" ], "text/html": [ "Changes to your `wandb` environment variables will be ignored because your `wandb` session has already started. For more information on how to modify your settings with `wandb.init()` arguments, please refer to the W&B docs." ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mayoola\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Tracking run with wandb version 0.13.1" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Run data is saved locally in /content/wandb/run-20220815_183650-1vg0u8vz" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Syncing run bart-large-xsum-samsum to Weights & Biases (docs)
" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "
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EpochTraining LossValidation LossRouge1Rouge2RougelRougelsumGen Len
01.3833001.47444353.27280028.59070043.98910048.67970025.975600
11.0762001.42485354.42930029.31250044.66260050.00310030.932800
20.8555001.47117154.42110029.53610045.11760050.06590030.431500

" ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "Saving model checkpoint to test-dialogue-summarization/checkpoint-500\n", "Configuration saved in test-dialogue-summarization/checkpoint-500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-500/special_tokens_map.json\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-1000\n", "Configuration saved in test-dialogue-summarization/checkpoint-1000/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-1000/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-1000/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-1000/special_tokens_map.json\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-1500\n", "Configuration saved in test-dialogue-summarization/checkpoint-1500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-1500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-1500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-1500/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-500] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `BartForConditionalGeneration.forward` and have been ignored: id, dialogue, summary. If id, dialogue, summary are not expected by `BartForConditionalGeneration.forward`, you can safely ignore this message.\n", "***** Running Evaluation *****\n", " Num examples = 818\n", " Batch size = 4\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-2000\n", "Configuration saved in test-dialogue-summarization/checkpoint-2000/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-2000/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-2000/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-2000/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-1000] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-2500\n", "Configuration saved in test-dialogue-summarization/checkpoint-2500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-2500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-2500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-2500/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-1500] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-3000\n", "Configuration saved in test-dialogue-summarization/checkpoint-3000/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-3000/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-3000/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-3000/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-2000] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-3500\n", "Configuration saved in test-dialogue-summarization/checkpoint-3500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-3500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-3500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-3500/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-2500] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `BartForConditionalGeneration.forward` and have been ignored: id, dialogue, summary. If id, dialogue, summary are not expected by `BartForConditionalGeneration.forward`, you can safely ignore this message.\n", "***** Running Evaluation *****\n", " Num examples = 818\n", " Batch size = 4\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-4000\n", "Configuration saved in test-dialogue-summarization/checkpoint-4000/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-4000/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-4000/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-4000/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-3000] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-4500\n", "Configuration saved in test-dialogue-summarization/checkpoint-4500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-4500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-4500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-4500/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-3500] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-5000\n", "Configuration saved in test-dialogue-summarization/checkpoint-5000/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-5000/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-5000/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-5000/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-4000] due to args.save_total_limit\n", "Saving model checkpoint to test-dialogue-summarization/checkpoint-5500\n", "Configuration saved in test-dialogue-summarization/checkpoint-5500/config.json\n", "Model weights saved in test-dialogue-summarization/checkpoint-5500/pytorch_model.bin\n", "tokenizer config file saved in test-dialogue-summarization/checkpoint-5500/tokenizer_config.json\n", "Special tokens file saved in test-dialogue-summarization/checkpoint-5500/special_tokens_map.json\n", "Deleting older checkpoint [test-dialogue-summarization/checkpoint-4500] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `BartForConditionalGeneration.forward` and have been ignored: id, dialogue, summary. If id, dialogue, summary are not expected by `BartForConditionalGeneration.forward`, you can safely ignore this message.\n", "***** Running Evaluation *****\n", " Num examples = 818\n", " Batch size = 4\n", "\n", "\n", "Training completed. Do not forget to share your model on huggingface.co/models =)\n", "\n", "\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "TrainOutput(global_step=5523, training_loss=1.1176997911189748, metrics={'train_runtime': 4282.7561, 'train_samples_per_second': 10.32, 'train_steps_per_second': 1.29, 'total_flos': 2.609612124409037e+16, 'train_loss': 1.1176997911189748, 'epoch': 3.0})" ] }, "metadata": {}, "execution_count": 16 } ] }, { "cell_type": "code", "metadata": { "id": "ceEjkJM0b0FS", "colab": { "base_uri": "https://localhost:8080/", "height": 300 }, "outputId": "029236fd-a28f-4e64-d396-11913936ace5" }, "source": [ "trainer.evaluate()" ], "execution_count": 17, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "The following columns in the evaluation set don't have a corresponding argument in `BartForConditionalGeneration.forward` and have been ignored: id, dialogue, summary. If id, dialogue, summary are not expected by `BartForConditionalGeneration.forward`, you can safely ignore this message.\n", "***** Running Evaluation *****\n", " Num examples = 818\n", " Batch size = 4\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "

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Run summary:


eval/gen_len30.4315
eval/loss1.47117
eval/rouge154.4211
eval/rouge229.5361
eval/rougeL45.1176
eval/rougeLsum50.0659
eval/runtime238.6829
eval/samples_per_second3.427
eval/steps_per_second0.859
train/epoch3.0
train/global_step5523
train/learning_rate0.0
train/loss0.8555
train/total_flos2.609612124409037e+16
train/train_loss1.1177
train/train_runtime4282.7561
train/train_samples_per_second10.32
train/train_steps_per_second1.29

" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Synced bart-large-xsum-samsum: https://wandb.ai/ayoola/bart_large_xsum_samsum/runs/1vg0u8vz
Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "Find logs at: ./wandb/run-20220815_183650-1vg0u8vz/logs" ] }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login" ], "metadata": { "id": "rNHeK_85Hexx" }, "execution_count": 22, "outputs": [] }, { "cell_type": "code", "source": [ "notebook_login()" ], "metadata": { "id": "SqajLxR6He6b", "outputId": "1f697656-747b-4fbc-8c2a-7d3e742d83d9", "colab": { "base_uri": "https://localhost:8080/", "height": 327, "referenced_widgets": [ "e8bcdcb3fde44602b14b56bee31640a8", "ff5fb4f3e88945519acd3ddabbab6fe3", "01e39f0a1fc5451abacc189f239c62b1", "1208a58cdf7441ab8c2f37f863c45174", "2af0897110a248faaf4c8d1531b903cb", "c5b389df71ac4078855de4d82ffc2905", "5a46713386054278837116c2bf6a9877", "de6dd8f1aed145fca0495e4fbc5acb39", "6602e0387799434ab6349cc169e349b6", "8f59442ac94f405bbf4b1939e4ef293c", "a4fca7d79c394ef7ade2a833bde4ed36", "e29b722358444c75a9e5e895105f203e", "c02f97f6b7154078a9552497fc451390", "1a125fda3f0c4c4ea41ba62e4299d6c9" ] } }, "execution_count": 23, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Login successful\n", "Your token has been saved to /root/.huggingface/token\n", "\u001b[1m\u001b[31mAuthenticated through git-credential store but this isn't the helper defined on your machine.\n", "You might have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal in case you want to set this credential helper as the default\n", "\n", "git config --global credential.helper store\u001b[0m\n" ] } ] }, { "cell_type": "code", "source": [ "model.push_to_hub(\"clyde\")" ], "metadata": { "id": "-FgslojBJ0c5", "outputId": "0f9908ba-4749-4dce-9569-c217a3ffe13d", "colab": { "base_uri": "https://localhost:8080/", "height": 404, "referenced_widgets": [ "a7cf6106216141b88b20cd1ef7695d11", "c9b6054279e04ba5866749631b22782f", "2724838e7f724941854ea149c677cd26", "6dd8ce3664874c5892aab35df099171a", "9e2e77dfa6074f62af0b0c1d07ef467f", "22e028cc89c24f5383b5abcbdc09d119", "fecb2bd873824af589bffa701c10048e", "755dd21c708545628d8fa9e048fdaed0", "de136514cc23460b85eb59c2b1bffe7c", "190ab6d43a0241bab3b2b80d517e4868", "bb3cc478330445e4b223d8b38c43b438", "4bcebaf0444543f4ace87f218b4d94e5", "ea38305f9ee04bdbaae396d86eaa545d", "aef9c132cd29404f9c03e747c15805d5", "2105bb9ed09e4f028d3a81a76455d8a8", "07a033bd8a7e46d68e6e73b7dfdf472d", "5923d73cb86b42098d9a4035db682cdf", "f86bd7533adb42899e644fc7157aef82", "77e3fae31b6c49e2ad47cc58f7583ae3", "9c54334f671144abbcaa97b2a954268a", "40639549cd2549a085b4c8d7df9d9143", "98629ced08e741a2b3fad86ee4ebffc0", "d00906353ff4498cb32ef260e50af75c", "3a45fadea26f43ff92d8f926f3a3d367", "cc74a0c469654102a92bdf2e7e6a2c94", "706756528d5a4ed1ba74392d9acb7178", "3154d9492ca846e7b2a02b8e30a8045a", "cda954cda82c4aa084d3d1a1702951a2", "3ad8a19b66a1431fa8ff505e97f8d96f", "0a5ba573a19144a9b4497fcea36ee932", "b9f8fae54afc456fa0e318aedcddea8e", "222d65e2c7e54fab8c220e26f0d452e9", "b505286b14734c438080036c12f4fdcb", "043fb7b71ed24217a1e8fcc99a7fce88", "6ee461137eba4e88b55c6d620e70d18b", "08cfc01922b643e6ba05e7f1ff698c98", "fccb68c17aa34658bec0b79052971172", "4d29f9bcf16647b9bd902c1b97ae5f61", "3e65ec01943042b7a05048750a3707d0", "d0093af426c74ad1bf06945e6e452c7b", "6e94f90693944effb4b20bcbbb053a9f", "e8a45680d3ef4afdb4d2a38077f9e30a", "7f2c0b39be624c2aa97732efb5806653", "c4266415615b466ca5216f8311e04a75", "615446d5ef5640b49f7155d5f26d5705", "aa57df9b125c49339679de31477b15a2", "fb1358aa45f74b519400a3bfb8e18152", "47b1ce9368ee4dbc89a070440b4a49e7", "84f53d18c8764b20a6d8916219f1c64b", "2da0c2d6f1f8418bae6d7a93f1d4e035", "4afef9a3fc24458a80123beef80b58d1", "c4f84ba7cd77435788ab5c07878201ef", "5169f864b8e14e4cb32626cc442dfb19", "63999e902d684f6b823d557bea3e16b5", "3eb6da7f84d64ba7b74ad5ef717a9025" ] } }, "execution_count": 43, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "Configuration saved in clyde/config.json\n", "Model weights saved in clyde/pytorch_model.bin\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Upload file optimizer.pt: 0%| | 3.33k/3.03G [00:00 main\n", "\n", "WARNING:huggingface_hub.repository:remote: Scanning LFS files for validity, may be slow... \n", "remote: LFS file scan complete. \n", "To https://huggingface.co/Ayoola/clyde\n", " 1cf1d86..7d9a15b main -> main\n", "\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "'https://huggingface.co/Ayoola/clyde/commit/7d9a15bad003beb24e7c06238c5a4857c505538e'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 43 } ] }, { "cell_type": "code", "source": [ "" ], "metadata": { "id": "QWy8BsqcIB1x" }, "execution_count": 24, "outputs": [] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "ecb7fc9d07ac44248c795d95cf949231", "f25c9782e4fe46368ccb154ba274c1ec", "b62ea6f0bb3b407f91cec0a6331e7fe4", "59527de736ed40b0986fce03e5a4bfda", "cd7572ef160b4b5fbfa2d85b97a77b09", "0ded7010ea504705ab6e5c9504ec8aed", "c97be7687f6e4112a41f4e1dfd112080", "a6ab1267ae074a5b83d5f7e938d28b45", "1bb48d1406a24252ae8fb7822459475b", "59aec02001334c419ba620ac4aadab1b", "7285bc26557a43cc9377db331638e51f", "7bbdc485cd3849c28a368821325cdbe5", "86f4deead37547ccbced6089224b29f8", "cc4e47b701394aa9b7f1c70f98fd8157", "cfb7f94663ac4124b799a90223563ba2", "6a050fd4b84e4c119fe6e887ed8c0eb6", "b096fc4aa1d9428aaa5937f112efa924", "4ab2bc00ab9b463895fa2b084e0d99c2", "53bfbfd5a8f74f1c9246022b8363cf0d", "67b9fb90c100467f9455472b4f81215a", "6d438bc44c544e708d2b19521be04f24", "85a0fd0c27f547919426a1c358c0178c", "b6098cff9a5b431aa82b859082616d37", "4084228fe2854cafa3d69a2d88e4287b", "ee80c0d34c9642c08639043c844cdd63", "44d1a1ab883c4c17a310dc14047cb79b", "7f48b60e5a5c406d86ef06f2a2b478ba", "936bf243d8834d0db8cb1e07208c7bce", "c0d68052f38343df98f26013848588e4", "e7866bbac2704a6e9b9924a282fc9dbf", "4e9389fe6d9b49a89e30084bf918cc18", "bfa3df1dd10f4a2781c48bc49affa4ea", "14c0035a91384122b47d13ea1b2c1890", "318676b785f04b1caf87c9cd5b4b2e63", "b99cec46a1ce4cbd87f0e1fd0cf37f62", "1dff21769676463ca66920e3b33279a0", "4c046bf10f6c404ba36f26e106516b26", "468d382a98b145238a3a3ef064f48fcc", "74a7e17a1f3d4590a81cf26c40aa678b", "43632cb67cad4613bfc6a81ab51a02c7", "eee0dc645376472086c5e8eb55148661", "7613573a4d7645eeaad8124149a7b6be", "a200630b98b44eb7b4d3cab51f0d9d45", "51072b54beb44e51941a52a9075fa455" ] }, "id": "JPEM-oeaq6Ka", "outputId": "24afe383-1669-4910-ca96-e004b3fa3978" }, "source": [ "from transformers import pipeline\n", "\n", "summarizer = pipeline(\"summarization\", model=\"Ayoola/clyde\")\n", "conversation = '''che: Hey, have you built the model?\n", "Ayo: Lemme check\n", "Ayo: Sorry, i have not.\n", "Ayo: I will tomorrow\n", "Ayo: i think we need more data\n", "Ayo: but i may be wrong\n", "Ayo: it is just an hypothesis\n", "che: If you say so..\n", "che: i am working converting the transcriptions to the right format\n", "Ayo: Awesome 🙂\n", "che: see you soon\n", "che: Bye\n", "Ayo: Bye bye \n", "'''\n", "summarizer(conversation)" ], "execution_count": 44, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "loading configuration file https://huggingface.co/Ayoola/clyde/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3925684a81d704d784ffab4bdb4097fcb08c20930badd3337c07782d0eb5d666.9b8c0031ba05106ba501a98678111e6eb1447b983b16dfba9960cba29742333d\n", "Model config BartConfig {\n", " \"_name_or_path\": \"Ayoola/clyde\",\n", " \"_num_labels\": 3,\n", " \"activation_dropout\": 0.0,\n", " \"activation_function\": \"gelu\",\n", " \"add_bias_logits\": false,\n", " \"add_final_layer_norm\": false,\n", " \"architectures\": [\n", " \"BartForConditionalGeneration\"\n", " ],\n", " \"attention_dropout\": 0.0,\n", " \"bos_token_id\": 0,\n", " \"classif_dropout\": 0.0,\n", " \"classifier_dropout\": 0.0,\n", " \"d_model\": 1024,\n", " \"decoder_attention_heads\": 16,\n", " \"decoder_ffn_dim\": 4096,\n", " \"decoder_layerdrop\": 0.0,\n", " \"decoder_layers\": 12,\n", " \"decoder_start_token_id\": 2,\n", " \"dropout\": 0.1,\n", " \"early_stopping\": true,\n", " \"encoder_attention_heads\": 16,\n", " \"encoder_ffn_dim\": 4096,\n", " \"encoder_layerdrop\": 0.0,\n", " \"encoder_layers\": 12,\n", " \"eos_token_id\": 2,\n", " \"eos_token_ids\": [\n", " 2\n", " ],\n", " \"forced_eos_token_id\": 2,\n", " \"gradient_checkpointing\": false,\n", " \"id2label\": {\n", " \"0\": \"LABEL_0\",\n", " \"1\": \"LABEL_1\",\n", " \"2\": \"LABEL_2\"\n", " },\n", " \"init_std\": 0.02,\n", " \"is_encoder_decoder\": true,\n", " \"label2id\": {\n", " \"LABEL_0\": 0,\n", " \"LABEL_1\": 1,\n", " \"LABEL_2\": 2\n", " },\n", " \"max_length\": 62,\n", " \"max_position_embeddings\": 1024,\n", " \"min_length\": 11,\n", " \"model_type\": \"bart\",\n", " \"no_repeat_ngram_size\": 3,\n", " \"normalize_before\": false,\n", " \"normalize_embedding\": true,\n", " \"num_beams\": 6,\n", " \"num_hidden_layers\": 12,\n", " \"output_past\": true,\n", " \"pad_token_id\": 1,\n", " \"prefix\": \" \",\n", " \"replacing_rate\": 0,\n", " \"scale_embedding\": false,\n", " \"static_position_embeddings\": false,\n", " \"student_decoder_layers\": null,\n", " \"student_encoder_layers\": null,\n", " \"task_specific_params\": {},\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.21.1\",\n", " \"use_cache\": true,\n", " \"vocab_size\": 50264\n", "}\n", "\n", "loading configuration file https://huggingface.co/Ayoola/clyde/resolve/main/config.json from cache at /root/.cache/huggingface/transformers/3925684a81d704d784ffab4bdb4097fcb08c20930badd3337c07782d0eb5d666.9b8c0031ba05106ba501a98678111e6eb1447b983b16dfba9960cba29742333d\n", "Model config BartConfig {\n", " \"_name_or_path\": \"Ayoola/clyde\",\n", " \"_num_labels\": 3,\n", " \"activation_dropout\": 0.0,\n", " \"activation_function\": \"gelu\",\n", " \"add_bias_logits\": false,\n", " \"add_final_layer_norm\": false,\n", " \"architectures\": [\n", " \"BartForConditionalGeneration\"\n", " ],\n", " \"attention_dropout\": 0.0,\n", " \"bos_token_id\": 0,\n", " \"classif_dropout\": 0.0,\n", " \"classifier_dropout\": 0.0,\n", " \"d_model\": 1024,\n", " \"decoder_attention_heads\": 16,\n", " \"decoder_ffn_dim\": 4096,\n", " \"decoder_layerdrop\": 0.0,\n", " \"decoder_layers\": 12,\n", " \"decoder_start_token_id\": 2,\n", " \"dropout\": 0.1,\n", " \"early_stopping\": true,\n", " \"encoder_attention_heads\": 16,\n", " \"encoder_ffn_dim\": 4096,\n", " \"encoder_layerdrop\": 0.0,\n", " \"encoder_layers\": 12,\n", " \"eos_token_id\": 2,\n", " \"eos_token_ids\": [\n", " 2\n", " ],\n", " \"forced_eos_token_id\": 2,\n", " \"gradient_checkpointing\": false,\n", " \"id2label\": {\n", " \"0\": \"LABEL_0\",\n", " \"1\": \"LABEL_1\",\n", " \"2\": \"LABEL_2\"\n", " },\n", " \"init_std\": 0.02,\n", " \"is_encoder_decoder\": true,\n", " \"label2id\": {\n", " \"LABEL_0\": 0,\n", " \"LABEL_1\": 1,\n", " \"LABEL_2\": 2\n", " },\n", " \"max_length\": 62,\n", " \"max_position_embeddings\": 1024,\n", " \"min_length\": 11,\n", " \"model_type\": \"bart\",\n", " \"no_repeat_ngram_size\": 3,\n", " \"normalize_before\": false,\n", " \"normalize_embedding\": true,\n", " \"num_beams\": 6,\n", " \"num_hidden_layers\": 12,\n", " \"output_past\": true,\n", " \"pad_token_id\": 1,\n", " \"prefix\": \" \",\n", " \"replacing_rate\": 0,\n", " \"scale_embedding\": false,\n", " \"static_position_embeddings\": false,\n", " \"student_decoder_layers\": null,\n", " \"student_encoder_layers\": null,\n", " \"task_specific_params\": {},\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.21.1\",\n", " \"use_cache\": true,\n", " \"vocab_size\": 50264\n", "}\n", "\n", "loading weights file https://huggingface.co/Ayoola/clyde/resolve/main/pytorch_model.bin from cache at /root/.cache/huggingface/transformers/6974d0c32a3900e59ce81fe93488da86351c060548f66b355dfce8572b0616e3.d4e32efdf3309375c2f467e1288a2d31e8e14e1cb021c70a255d59c8dc532c47\n", "All model checkpoint weights were used when initializing BartForConditionalGeneration.\n", "\n", "All the weights of BartForConditionalGeneration were initialized from the model checkpoint at Ayoola/clyde.\n", "If your task is similar to the task the model of the checkpoint was trained on, you can already use BartForConditionalGeneration for predictions without further training.\n", "https://huggingface.co/Ayoola/clyde/resolve/main/tokenizer_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpt4776gsd\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading tokenizer_config.json: 0%| | 0.00/390 [00:00