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"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": [ "fbbec5f3e1144329a32c7bc626d43564", "521a126841b148fc809b72c210a692e6", 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"6c905f7c39334836858971a05a854602", "59c8e3962805466ba19b0f98092cb198", "777e190900814b6fbad8cfddede65520", "f27a53e4b08747fe8f7a4b62ce05224b", "5d579cd6eed04e45912cdacf3a074f47", "bedc323939c0434281c0365edfc0a486", "71681c4009fb47cd8cefd1735e7f1d4e", "c4d293663a16418d8cd99275325bd801", "f22c26d58cf7407fbe9b7d6932891b2b", "5b81fba4de0d4efd8ccbc3767be602e0", "d0c6ae09517647fe9c87bcb3376d2ccb", "61f3af66c559474eacd4b9f4fe1c454c", "8e311b20e6e943aeb43c9ed21a8525ae", "12d37645fd8f410da138584fed410e13", "ab6744039c3745d0810f1bb82b1466bf", "66f230efa90c4e299c6db623f8af6e4f", "29ed2aaf50d24af8be64f3b02d9f8c69", "cc267f24f3534aa9ad53cb0e2f140362", "4b13b44a8a7d4fd28c87a2477489e41f", "aa658c8e22f048d6806280542264285a", "6899488d14eb42ff8b46c386d72e728e", "e99a90c99bc5467babc019d639e94f65", "a3f3ca53afca4805817c21d149ccde34", "f09dbf78fb344014ba74be247924d127", "fbbf5cfb0f4e41619f2faff308b8e68d", "11d33d185a3741768f52254c282ea58a", "ddf33b7311fc4c7da5373a8c940a297f", "f7c4e6d5537a4180bf00d89da3bdeedd", "35e756fd317f4c16aad24cb97729739f", "94b557ca3b0845a69d4647ac246e50c1", "2f5df2861e1f4e18a1172262e44430a2", "45e55efdd1d847cf8a701b9360527c07", "930d7294753d40428255d9df29575dc2", "9824c55191614126a92f53c310427930", "a30e73edd18a454f8ea85fd54e5d44cd", "add70381d15c4c0f95a4235bad9ef769", "9a5c027477e444388eea3e2c6933d682", "fcbe430146c84ee284f7502f74646693", "9d6759560ad84d7baec54f5fd715486e", "cc87437d42304f70a50fad9b25e66e70", "975fdebf3c404ab186915814be799f15", "eb80838d87b742b3887676035cf6d884", "33ed915ca8e14e9fa8d200d808be8ebb", "4625a608d3354a58aa136b22a6c903b7", "9fad83e033ff4ff891f4044f53fad033", "f23a582f2ae2410081b2fa55c0b0be3b", "98675d6f5f394a78a656c3ba4620afc5", "f613fb3aca4f436aaf162e2c351a479f", "93a995905a7d43dab33e0ad83ce7db54", "8a12aa0c5d66497a883dec4fbb104f6a", "fbba11428698450abe6e3eeffc73ebd7", "0d11f03007ac48348b9ca4361bf60c8d", "ce03c69693b74b1da47320a145d5af36", "6f6b0039f9d140f1ac8de0820358acd0", "fbfb47e83d2242a1bc208f6bc6ff3d7e", "74a2663ee6304c93a6046230cff11112", "f3fef4c3bd4e4c5596bb49b394b93c28", "f368e2ef42c6481882738fec70934ed5", "81c83d6eb3874bd4bdec767629380286", "275dc9b148c84a5aab70e0e2f26a0dc0", "84dd9145a2e14bb1be15c829b4fcf4a4", "607497651ffe49cda57e5c97f80c0086", "5602ce8ff0574f7bb38abaaa22016cfb", "6d549bdfaf00486a8bcb0fb651e96f7a", "b094240cefac4c09a175614d10e4597f", "c532b1dc063d402ea582404ce7736f64", "6f51fe0500bf4c538dc08f8ddff7fd2c", "4fc99f322eb2429d8a1dc62b9e049822", "c405624db06b481a9bdcef378a15aff8", "16cdeaaa224e4e678b91e38517b08e32" ] }, "id": "hnwqYEFnhji5", "outputId": "c2ff8875-9db0-4c9b-eaa1-0eee4900ecc9" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "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 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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": [] } ] }