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+ "!nvidia-smi"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "M2b-7B0PjEvG",
+ "outputId": "0113dea3-3ff1-4cce-cb3e-062a7691fa00"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Thu Jan 27 18:50:08 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 39C 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": "42f3f790-8c04-4a1a-d7e8-26ba2f0d3626"
+ },
+ "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 1s (2,440 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": [
+ "ca3d8b2c83fd4dc992e866c692750b0a",
+ "d36eb844e8a64732bdd5ff333b6b80eb",
+ "8ac172b545d342df8df31641a9631009",
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+ "1a78b5324d3541caba1d875e4f5b1f92",
+ "0dfa212090a14912a217f338eadd5b45",
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+ "b7f4f0b5788a4b0696f0af2dc04d6c37",
+ "acd5f5ba75d843e49235bebfd179574e"
+ ]
+ },
+ "id": "1CCVxM2-hLbE",
+ "outputId": "f8461c13-8fac-47af-b78d-122aed0c9429"
+ },
+ "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\", \"mr\", split=\"train+validation\", use_auth_token=True)\n",
+ "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"mr\", split=\"test\", use_auth_token=True)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 357,
+ "referenced_widgets": [
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+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "34e092a60d234970b9acc41bf01d12a5",
+ "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-mr/commit/579700a90edf82cbacef673e7e305ea8386f7bf8'"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 38
+ }
+ ]
+ },
+ {
+ "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": [
+ "2029fca60e2846de9e7fdcab44747a84",
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+ ]
+ },
+ "id": "Uxt4G7XweZxf",
+ "outputId": "5b1d33cc-93dc-4334-8748-612c2b23253b"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "2029fca60e2846de9e7fdcab44747a84",
+ "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": "f5ea16e6cbdc4c6187c64207649a489b",
+ "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": [
+ "752699eea4944dfc87d383b8709fb810",
+ "0f8fe3ebdac74e299694511ef3c3582e",
+ "58f899a7b6c74db0b2268a442c18be35",
+ "84f7e373503743a8ac33cc70d1ffeb76",
+ "ee945c3b01c0490a9ccfee68eaaa3283",
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+ "160248765b014defaaa4bfbce207a8ee",
+ "127537cdb5214476ba1f04ca6273265b",
+ "5dfad1bf272d4914a1e4c99b32f799ff",
+ "5e1e2943cd5f482fb055085b21339a63",
+ "372186370fe94f4caa0fed0585aa52ed"
+ ]
+ },
+ "id": "tHAXlHO1ez7Z",
+ "outputId": "b264fe96-9b0d-4c12-a439-059f7a6236a1"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "752699eea4944dfc87d383b8709fb810",
+ "version_minor": 0,
+ "version_major": 2
+ },
+ "text/plain": [
+ "Downloading: 0%| | 0.00/1.91k [00:00\n",
+ " \n",
+ " \n",
+ " [4400/4400 6:34:02, Epoch 200/200]\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " | Step | \n",
+ " Training Loss | \n",
+ " Validation Loss | \n",
+ " Wer | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 400 | \n",
+ " 3.737800 | \n",
+ " 3.504736 | \n",
+ " 1.000000 | \n",
+ "
\n",
+ " \n",
+ " | 800 | \n",
+ " 3.170700 | \n",
+ " 2.616584 | \n",
+ " 0.991175 | \n",
+ "
\n",
+ " \n",
+ " | 1200 | \n",
+ " 1.494200 | \n",
+ " 0.577774 | \n",
+ " 0.692740 | \n",
+ "
\n",
+ " \n",
+ " | 1600 | \n",
+ " 1.205800 | \n",
+ " 0.516843 | \n",
+ " 0.636181 | \n",
+ "
\n",
+ " \n",
+ " | 2000 | \n",
+ " 1.055800 | \n",
+ " 0.510508 | \n",
+ " 0.606899 | \n",
+ "
\n",
+ " \n",
+ " | 2400 | \n",
+ " 0.948800 | \n",
+ " 0.515087 | \n",
+ " 0.608905 | \n",
+ "
\n",
+ " \n",
+ " | 2800 | \n",
+ " 0.858800 | \n",
+ " 0.515661 | \n",
+ " 0.598877 | \n",
+ "
\n",
+ " \n",
+ " | 3200 | \n",
+ " 0.799100 | \n",
+ " 0.517909 | \n",
+ " 0.574007 | \n",
+ "
\n",
+ " \n",
+ " | 3600 | \n",
+ " 0.754500 | \n",
+ " 0.534822 | \n",
+ " 0.574007 | \n",
+ "
\n",
+ " \n",
+ " | 4000 | \n",
+ " 0.714400 | \n",
+ " 0.551771 | \n",
+ " 0.572403 | \n",
+ "
\n",
+ " \n",
+ " | 4400 | \n",
+ " 0.704100 | \n",
+ " 0.547911 | \n",
+ " 0.574007 | \n",
+ "
\n",
+ " \n",
+ "
"
+ ],
+ "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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-400\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-400/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-400/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-400/preprocessor_config.json\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-800\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-800/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-800/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-800/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-1200\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1200/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1200/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1200/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-1600\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1600/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1600/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-1600/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-2000\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2000/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2000/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2000/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-2400\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2400/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2400/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2400/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-2800\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2800/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2800/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-2800/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-3200\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3200/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3200/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3200/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-3600\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3600/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3600/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-3600/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-4000\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4000/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4000/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4000/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/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 = 306\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr/checkpoint-4400\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4400/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4400/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/checkpoint-4400/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-mr/checkpoint-4000] 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=4400, training_loss=1.8104798316955566, metrics={'train_runtime': 23651.2936, 'train_samples_per_second': 5.902, 'train_steps_per_second': 0.186, 'total_flos': 2.4058662657177895e+19, 'train_loss': 1.8104798316955566, 'epoch': 200.0})"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 53
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "trainer.push_to_hub()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 342,
+ "referenced_widgets": [
+ "900220d29d30456d9530a74324ca3eb8",
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+ },
+ "id": "1DzGjKHifPGK",
+ "outputId": "f184ae60-cfd8-46b2-90f9-b41ca9c8da61"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-mr\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-mr/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-mr/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": "900220d29d30456d9530a74324ca3eb8",
+ "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': 'mr'}}\n",
+ "To https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-mr\n",
+ " 60f764e..fb33813 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-mr/commit/60f764e9872c42651f3f4144c8b0993a862d4d3b'"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 54
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ ""
+ ],
+ "metadata": {
+ "id": "93NnxhS_1EIV"
+ },
+ "execution_count": null,
+ "outputs": []
+ }
+ ]
+}
\ No newline at end of file