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"|-------------------------------+----------------------+----------------------+\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 40C P0 30W / 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": { + "id": "k6Ao2XfngKmI", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "5e3d4c99-5dfe-4e43-ccb5-76e7bdd019b5" + }, + "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 2s (928 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": { + "id": "1CCVxM2-hLbE", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 359, + "referenced_widgets": [ + "39e1693dfe364c898f855a0706278262", + "93228b298bb74a1f85341d728f9a05e4", + "20042b9ba890434ca76d853f95e4ffe7", + "4954c5e13785448ea4821396c9f1b466", + "e2f1953e779148e09ea69d5ec4dc847a", + "ba52e726328847b08bbbf1c30e59c9fd", + "c37068c8f8e74da18bec74dcb7451d66", + "fc19041cb6544158b92e4f322c33ae44", + "f134c5e6f443443babb01556ff0facbc", + "f4eddb2180a245f8ac3b7d4b7ccb83f6", + "3b237748c2344b8c8cd7dec486f5043e", + "f98fde11c94d4128a1ee24cec5b2c339", + "379dccd4e0af4f2ca6971ef7970f20fd", + "276b07821d4f4b4594e485237b920c92", + "62424b7d68124d94b232eaaab9601ff9", + "984d56a0e4cd4f089af687f2769f0f45", + "6a913847fd0e4369b2459df029614b23" + ] + }, + "outputId": "2441b8a3-6e54-424c-b564-835fef5754e7" + }, + "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" + ], + "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\", \"ha\", split=\"train+validation\", use_auth_token=True)\n", + "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"ha\", split=\"test\", use_auth_token=True)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 377, + "referenced_widgets": [ + 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"390bfa1bc430443f94d1775fe3534c29", + "e199c3fd19b94ac7bb8c59b5efe01ff7", + "306ab39347064da58878fd1e1131bddb", + "3a992683baf446dd9f49fa0bc582abfe", + "1e1a5c83c3014ed9a787a1f58717717a", + "9dc7b748277e4e868ef56c9f017f5e6f", + "21ce97998c30482689936d37d6eee4cb", + "e0cf597caf894190b1627502c79e5aff", + "3b84f16bd8e0435f91743dc218cd320b", + "ec1ae1cf60d44343992908b606500b5c", + "ad53ad9be8fc4078b5de8ab87d0241a9", + "ea8db7f21cab4c91b7dc7947075e347a", + "000bcf0674a14065aedae6f7a696369f", + "3573d7dc45144df28a0ebc74090420d8", + "ea01665ced9748e499211fd1523bf000", + "f0a16554bc024808bf6ae630da486eec", + "eff2ed8a368140a58c174ceb1e69e563", + "fb81359cc21a48a19abea42888e6f8c4", + "8865005ef8f94f30b4874608617a7d81", + "cacb0214e531475d91a4c22a1602e679", + "cd9971a455694057bb3e29ac2acb621a" + ] + }, + "id": "hnwqYEFnhji5", + "outputId": "31e3bebe-37e9-46ad-e04b-b9d3180c8970" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c2a6609c04b04e8d827133334ccf81a2", + "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-ha-cv8/commit/64ff0d9d37d20d2363890c287a646dd76cd7bc50'" + ] + }, + "metadata": {}, + "execution_count": 19 + } + ] + }, + { + "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": [ + "7df77ec2e4434555bd625c88142624e5", + "dc29a68593a147fd9f7f197c6cf031f9", + "d8d90c6766c042e4ad95f7ebe65df9de", + "20502dcc8ab54fb28d66a12e59e460bc", + "782cea77e09c42d7841e6cb9f4d6ae4a", + "1c2f484100f44ef692ac60ea37ae795b", + "c1a9a4bb0183427d9d05500d293037c0", + "e8783d49b6264c2898088f3b01a1353d", + "ebef0bfa18aa4051a522b5f82e83b63d", + "771db2d95d5d496f9e4213cd03bdc83b", + "031d8484ee954cd7ad8020de6eace0b3", + "e30a930b820f4610acd41d2442b6cbfb", + "c61f0600f8144af89ff61a9ab4d8d58a", + "454c0a32562045c581236a327f7412de", + "3c2939ae8faa4303af7a5776ab1954d8", + "3876cc6f948843f8af7b7581801b253b", + "b4ff66868c6b4fe4a18a070a73ac54f8", + "dc16e0e94f1e4f9991389436cd80d68b", + "c922637427ee4b8681c541c12544ebe6", + "50b316dc7ab94ce4b405a92c45c57ae4", + "a55bf8ee695a4b8bb55f1cc3c96d3936", + "3d93eb28e2e943a791432a3affaa1bc6" + ] + }, + "id": "Uxt4G7XweZxf", + "outputId": "d98d6a8e-4a50-4ba5-9a3e-5f2f00e51d16" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7df77ec2e4434555bd625c88142624e5", + "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": "e30a930b820f4610acd41d2442b6cbfb", + "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": [ + "e167261c6b0643c1a9de50f92c0590ef", + "64222f57f03140b7b10a9927bb896098", + "025f169226ca4f54a88b56e6446b0f27", + "e25f1bbdf41b42e3838e81cc312e3098", + "6dbaf83cde894cfb95979e911705dd72", + "95fb631af45843f78daa5b9d0e3b59fa", + "916ff79ba8d94fc38f439e51c70ed483", + "311e38ea53854907ab63637bad7915c4", + "bf519997271a46ab9832502c8376a439", + "4d4f442c01694355b5e3660bd4cfd86e", + "cb72ee2808bf4ab39f53a3714a09ddf8" + ] + }, + "id": "tHAXlHO1ez7Z", + "outputId": "49b65f90-7ef0-458c-f343-87624c3a8f1b" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e167261c6b0643c1a9de50f92c0590ef", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/1.91k [00:00\n", + " \n", + " \n", + " [6100/6100 7:43:11, Epoch 100/100]\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
4002.9599002.8649911.000000
8002.7357002.7377490.995095
12001.3012000.6685550.711050
16001.0454000.5686420.613676
20000.9069000.5576090.581506
24000.8200000.5502260.559146
28000.7413000.5969900.558569
32000.6872000.5816530.542845
36000.6340000.5636440.531448
40000.6022000.5780250.522937
44000.5705000.6036290.532314
48000.5408000.6118670.533612
52000.5225000.6105440.526976
56000.5265000.6034070.523081
60000.5154000.6094430.523370

" + ], + "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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-400/preprocessor_config.json\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-1600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-2800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-3600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4400] 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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-4800] 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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5200] 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 = 892\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-6000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-6000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-6000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-6000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-ha-cv8/checkpoint-5600] 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=6100, training_loss=1.261003189086914, metrics={'train_runtime': 27800.0598, 'train_samples_per_second': 6.982, 'train_steps_per_second': 0.219, 'total_flos': 2.5645201559735407e+19, 'train_loss': 1.261003189086914, 'epoch': 100.0})" + ] + }, + "metadata": {}, + "execution_count": 34 + } + ] + }, + { + "cell_type": "code", + "source": [ + "trainer.push_to_hub()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 370, + "referenced_widgets": [ + "a7b6850a923647c3a1f3e63354b52dfc", + "475ac5f196c24148815e5a4e87d7c377", + "17042312fcab4786b948e781ad4d7ead", + "da397ad8e4a94ef597364090c4f8e6d0", + "356144ad9e524caf9fd1f0fa7dc80827", + "7b809d15d24b4f89aeff544a9e95f223", + "eed3462fb60f4c939b6e67a43da652fb", + "0eeb65b2bb1b4447a3116a23714051e8", + "1b405c99a9a24901aad625aa7912c22d", + "5d4a88ff15be4c2988009c03e976d44d", + "9adcf56c0f094295a0b82bffc8fcdc84", + "ca2bca9353b246a59b171d33861f8f43", + "d16c9b158aed4f28bb2a6b55702fd277", + "69fc532a8d024926a2fb294230872e38", + "17de61efffbb4da4b9972000dd434cbb", + "9186b22406d3404daeb55b059151ccad", + "4bba5e3ac21d48299d74ab3216103669", + "a57138b30a664ecd97784fe65206c387", + "4d3886eb267b48b5b2d888fd19e36e80", + "7e1217bc769e47908183e3ad2dc986e9", + "9d6447b1a5ba435681b6d0b5152a2324", + "6e1f7790f7254218a1eebbb8341bce06" + ] + }, + "id": "1DzGjKHifPGK", + "outputId": "71a60ef0-ad3a-43dd-902d-e515a5539edf" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Saving model checkpoint to wav2vec2-large-xls-r-300m-ha-cv8\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-cv8/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-ha-cv8/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-ha-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": "a7b6850a923647c3a1f3e63354b52dfc", + "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': 'ha'}}\n", + "To https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-ha-cv8\n", + " b10ee1b..19dfbde 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-ha-cv8/commit/b10ee1b13924b4dcb001e932e35520c79c438059'" + ] + }, + "metadata": {}, + "execution_count": 35 + } + ] + }, + { + "cell_type": "code", + "source": [ + "" + ], + "metadata": { + "id": "93NnxhS_1EIV" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file