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null, + "align_content": null, + "visibility": null, + "align_self": null, + "height": null, + "min_height": null, + "padding": null, + "grid_auto_rows": null, + "grid_gap": null, + "max_width": null, + "order": null, + "_view_module_version": "1.2.0", + "grid_template_areas": null, + "object_position": null, + "object_fit": null, + "grid_auto_columns": null, + "margin": null, + "display": null, + "left": null + } + } + } + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "code", + "source": [ + "!nvidia-smi" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "M2b-7B0PjEvG", + "outputId": "356dc298-adf9-45dc-f8d4-6e7230c9adf9" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Fri Jan 28 07:39:15 2022 \n", + "+-----------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 495.46 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 P100-PCIE... Off | 00000000:00:04.0 Off | 0 |\n", + "| N/A 32C P0 26W / 250W | 0MiB / 16280MiB | 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", + "execution_count": null, + "metadata": { + "id": "YZXTLpRzg8gp" + }, + "outputs": [], + "source": [ + "%%capture\n", + "!pip install datasets\n", + "!pip install transformers\n", + "!pip install huggingface_hub\n", + "!pip install torchaudio\n", + "!pip install librosa\n", + "!pip install jiwer" + ] + }, + { + "cell_type": "code", + "source": [ + "!apt install git-lfs" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "k6Ao2XfngKmI", + "outputId": "43373ff6-5dec-4fff-a901-50f57904bce1" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Reading package lists... Done\n", + "Building dependency tree \n", + "Reading state information... Done\n", + "The following NEW packages will be installed:\n", + " git-lfs\n", + "0 upgraded, 1 newly installed, 0 to remove and 37 not upgraded.\n", + "Need to get 2,129 kB of archives.\n", + "After this operation, 7,662 kB of additional disk space will be used.\n", + "Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 git-lfs amd64 2.3.4-1 [2,129 kB]\n", + "Fetched 2,129 kB in 0s (5,095 kB/s)\n", + "Selecting previously unselected package git-lfs.\n", + "(Reading database ... 155229 files and directories currently installed.)\n", + "Preparing to unpack .../git-lfs_2.3.4-1_amd64.deb ...\n", + "Unpacking git-lfs (2.3.4-1) ...\n", + "Setting up git-lfs (2.3.4-1) ...\n", + "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from huggingface_hub import notebook_login\n", + "\n", + "notebook_login()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 359, + "referenced_widgets": [ + "7d0ed64d754d4fc481bed395417edc15", + "9958085aec5440368287480dba1bbd4e", + "e94e40c9499845baa1d9d711e73cfdcd", + "9aea6ae48e884d718644114eea8c6611", + "d762d058bbdf43d0af3fb5e67e5c8de5", + "a3d6a787d9184c439b9c034c6fa4eea9", + "d8de48c32cf341418dbdbdb9db9db824", + "09d8d976778b4453b8ff742f2c9e9971", + "6f13512981ff41fba8b289d6d7eca09f", + "7a597a8b4d864d65bbaf4fa1100b02c2", + "a280b9a2682249738f6f2eb15fd6d20a", + "a6e013d2ed0b4cf2bea8bbfd6bec2618", + "18407d514e374950885ba62b53e34c80", + "fcb3ddc3d8bb4a35bd6db7d65da443b5", + "00b214a433ab40a09c6fa193da1e346c", + "ab9f726d58e941b88dd62fe34ba1c6a0", + "58c220e27a584bdfbc0ce46e7e34323d" + ] + }, + "id": "1CCVxM2-hLbE", + "outputId": "6b2fb826-f3aa-46ab-90dc-4cd0656badf2" + }, + "execution_count": null, + "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": [ + "from datasets import load_dataset, load_metric, Audio, concatenate_datasets" + ], + "metadata": { + "id": "HP3z-kMqhW49" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "!sudo rm -r /root/.cache" + ], + "metadata": { + "id": "OvVBJh9C5x_l" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "common_voice_train = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"ur\", split=\"train+validation\", use_auth_token=True)\n", + "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"ur\", split=\"test\", use_auth_token=True)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 357, + "referenced_widgets": [ + 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"application/vnd.jupyter.widget-view+json": { + "model_id": "fbbec5f3e1144329a32c7bc626d43564", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/10.1k [00:00 main\n", + "\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-ur-cv8/commit/5bf99be112910fb2e8f9b39fd16a7cbe06a29fc4'" + ] + }, + "metadata": {}, + "execution_count": 29 + } + ] + }, + { + "cell_type": "code", + "source": [ + "from transformers import Wav2Vec2FeatureExtractor\n", + "\n", + "feature_extractor = Wav2Vec2FeatureExtractor(feature_size=1, sampling_rate=16000, padding_value=0.0, do_normalize=True, return_attention_mask=True)" + ], + "metadata": { + "id": "1RseFfmleI3H" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from transformers import Wav2Vec2Processor\n", + "\n", + "processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)" + ], + "metadata": { + "id": "NGDrT6saeOqy" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "common_voice_train = common_voice_train.cast_column(\"audio\", Audio(sampling_rate=16_000))\n", + "common_voice_test = common_voice_test.cast_column(\"audio\", Audio(sampling_rate=16_000))" + ], + "metadata": { + "id": "nOpdod1weRfa" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def prepare_dataset(batch):\n", + " audio = batch[\"audio\"]\n", + "\n", + " # batched output is \"un-batched\"\n", + " batch[\"input_values\"] = processor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_values[0]\n", + " batch[\"input_length\"] = len(batch[\"input_values\"])\n", + " \n", + " with processor.as_target_processor():\n", + " batch[\"labels\"] = processor(batch[\"sentence\"]).input_ids\n", + " return batch" + ], + "metadata": { + "id": "KimgJI22eVYa" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "common_voice_train = common_voice_train.map(prepare_dataset, remove_columns=common_voice_train.column_names)\n", + "common_voice_test = common_voice_test.map(prepare_dataset, remove_columns=common_voice_test.column_names)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "8d263d6f0afc4b2ca6a0165d2170590f", + "ceef7e93f3b343deaf79794815e81bac", + "021733a253074d44bbfbb857e0ec072e", + "4bd9214d52544fa893877e9436cb2dae", + "575e084c857a49fb80c9796b567737b6", + "bc84411aa855463fb28196d2ec0c7d56", + "9ae69622d27a47b589497c677906a3ee", + "c4b159600b944b2e91942bb4e0a536ad", + "fc96db98c5e6473aae27eac20a2c883d", + "6237ef7804e446bb93b11f148a28e8cc", + "5a94a73c500d47cc9142dfc1a96c8f08", + "f2fd5c8c81d542db81469324c2f8a76e", + "b39b432f953e4aef85de0c8e4bd45d45", + "be0ad03b245f40f1860c09415c6561e0", + "96928740e7b54ca2af5d93ba09d551f3", + "856e1f4ed428460f87ab747f89afa205", + "090ba6d59f44466eb683c8d46f8f9009", + "9140167b93614eb6a7614be596ee78db", + "71dc3e620d6e413ebbbdb959a7236648", + "445396ef569045bbb6f7c78a4bcf5222", + "4f1b11c0cb314c6591b039218105f38a", + "19f01fa9aae648729243797104274026" + ] + }, + "id": "Uxt4G7XweZxf", + "outputId": "e01276c8-0f46-4580-cb74-badf01a495bb" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8d263d6f0afc4b2ca6a0165d2170590f", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f2fd5c8c81d542db81469324c2f8a76e", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import torch\n", + "\n", + "from dataclasses import dataclass, field\n", + "from typing import Any, Dict, List, Optional, Union\n", + "\n", + "@dataclass\n", + "class DataCollatorCTCWithPadding:\n", + " \"\"\"\n", + " Data collator that will dynamically pad the inputs received.\n", + " Args:\n", + " processor (:class:`~transformers.Wav2Vec2Processor`)\n", + " The processor used for proccessing the data.\n", + " padding (:obj:`bool`, :obj:`str` or :class:`~transformers.tokenization_utils_base.PaddingStrategy`, `optional`, defaults to :obj:`True`):\n", + " Select a strategy to pad the returned sequences (according to the model's padding side and padding index)\n", + " among:\n", + " * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single\n", + " sequence if provided).\n", + " * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the\n", + " maximum acceptable input length for the model if that argument is not provided.\n", + " * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of\n", + " different lengths).\n", + " \"\"\"\n", + "\n", + " processor: Wav2Vec2Processor\n", + " padding: Union[bool, str] = True\n", + " \n", + " def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:\n", + " # split inputs and labels since they have to be of different lenghts and need\n", + " # different padding methods\n", + " input_features = [{\"input_values\": feature[\"input_values\"]} for feature in features]\n", + " label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n", + "\n", + " batch = self.processor.pad(\n", + " input_features,\n", + " padding=self.padding,\n", + " return_tensors=\"pt\",\n", + " )\n", + " with self.processor.as_target_processor():\n", + " labels_batch = self.processor.pad(\n", + " label_features,\n", + " padding=self.padding,\n", + " return_tensors=\"pt\",\n", + " )\n", + "\n", + " # replace padding with -100 to ignore loss correctly\n", + " labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n", + "\n", + " batch[\"labels\"] = labels\n", + "\n", + " return batch" + ], + "metadata": { + "id": "k1hUL21-ecSE" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)" + ], + "metadata": { + "id": "3WErNElzezOc" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "wer_metric = load_metric(\"wer\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "41d754248e0d4d9d8fa85c8d7999e792", + "4d83150acd0840bebb2f127cb1ed1312", + "00c691966ac542ecaead8162471d95d9", + "1fe1280e32d144439379c43f9085e8a0", + "61fab252b7474bc982dd54add361b3db", + "692bdfa1044844b6b8cf307841562620", + "b9f6ae6d1e3d45ba8699a81e31d5ec8f", + "a534cb7eec3842f981be9eceece45775", + "656ec428767244e8a07552eb05977df0", + "98d670bc0e6242afbc84081829bdcf4a", + "3d7f99f5dd8a490582dec88238d32688" + ] + }, + "id": "tHAXlHO1ez7Z", + "outputId": "1cd21eba-0c45-4a16-cc32-2d2ed5db2567" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "41d754248e0d4d9d8fa85c8d7999e792", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/1.91k [00:00\n", + " \n", + " \n", + " [5000/5000 5:46:13, Epoch 199/200]\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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StepTraining LossValidation LossWer
4003.6269003.3245881.000000
8003.0546002.8147590.996299
12001.4589001.0236630.658401
16001.0911000.9524310.596595
20000.8879000.9826900.582161
24000.7467000.9922570.584012
28000.6427000.9987510.571429
32000.5685001.0872390.580681
36000.5068001.1194120.582161
40000.4630001.1138340.569208
44000.4212001.1232490.571429
48000.4056001.1443170.567728

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-400/preprocessor_config.json\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/preprocessor_config.json\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-1600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-2800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-3600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 341\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ur-cv8/checkpoint-4400] due to args.save_total_limit\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=5000, training_loss=1.5904918968200683, metrics={'train_runtime': 20780.7626, 'train_samples_per_second': 7.796, 'train_steps_per_second': 0.241, 'total_flos': 2.0716608264816038e+19, 'train_loss': 1.5904918968200683, 'epoch': 199.98})" + ] + }, + "metadata": {}, + "execution_count": 44 + } + ] + }, + { + "cell_type": "code", + "source": [ + "trainer.push_to_hub()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 342, + "referenced_widgets": [ + "de9dc0054a5b4d0bbaec91da45d4b5e2", + "e6a2c16b1e3648cbbb67350fc3631e8d", + "4028dc4d2139456e94815357047f8b30", + "80f3d8a180f84f469e2554d16b73524c", + "ad94cf0637474d3bb31b096ca34d4e35", + "3e954e6517604989a55c664877959c59", + "db766081e935432885e50bead6caebb7", + "4d4de124bf294674aa183c0b04503017", + "694952c1016d45bca0521cac40e3f0ea", + "94795d46ac0b41cba9c86fce2b6f595b", + "8881e61acde140ef9a17b32056b9cea9", + "a9c562139d0141d0ad8c97012d2afb2b", + "56589debc57c40e8be561b0e6031aee8", + "3e818fe37334429e8be642259870f6e1", + "8db9cd55f7a440668e17dc3697b41e79", + "0b5dc70ad76847a999106b6c92f542d7", + "885952c914ab43c4868434611522609b", + "c09382390edc4d07bc4f5a5db9a073dc", + "4c66c1d6da5f44bb9919cc1e1e5cc239", + "ee158ed07892420caa82bd0d1a521bee", + "bf6377640dd54dc8a4f0012927f4a588", + "abd88ac48e654ae492c7ff1fe5cd3d21" + ] + }, + "id": "1DzGjKHifPGK", + "outputId": "7060e1ac-cefd-446d-e970-1c24d7fb15b8" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ur-cv8\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ur-cv8/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ur-cv8/preprocessor_config.json\n", + "Several commits (2) will be pushed upstream.\n", + "The progress bars may be unreliable.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "de9dc0054a5b4d0bbaec91da45d4b5e2", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Upload file pytorch_model.bin: 0%| | 3.37k/1.18G [00:00 main\n", + "\n", + "Dropping the following result as it does not have all the necessary fields:\n", + "{'dataset': {'name': 'common_voice', 'type': 'common_voice', 'args': 'ur'}}\n", + "To https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-ur-cv8\n", + " 04cebec..6f2b149 main -> main\n", + "\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-ur-cv8/commit/04cebecbbe682de29ac6b0993680e6c7ace56345'" + ] + }, + "metadata": {}, + "execution_count": 45 + } + ] + }, + { + "cell_type": "code", + "source": [ + "" + ], + "metadata": { + "id": "93NnxhS_1EIV" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file