"
]
},
"metadata": {},
"execution_count": 37
}
],
"source": [
"import IPython.display as ipd\n",
"import numpy as np\n",
"import random\n",
"\n",
"rand_int = random.randint(0, len(common_voice_train)-1)\n",
"\n",
"print(common_voice_train[rand_int][\"sentence\"])\n",
"ipd.Audio(data=common_voice_train[rand_int][\"audio\"][\"array\"], autoplay=True, rate=16000)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "EE5jG9PVZmWU",
"outputId": "62287142-3ce2-486f-cf2a-3f3cd6bc5d69"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Target text: तुम ने टॉम को कहाँ भेजा\n",
"Input array shape: (32832,)\n",
"Sampling rate: 16000\n"
]
}
],
"source": [
"rand_int = random.randint(0, len(common_voice_train)-1)\n",
"\n",
"print(\"Target text:\", common_voice_train[rand_int][\"sentence\"])\n",
"print(\"Input array shape:\", common_voice_train[rand_int][\"audio\"][\"array\"].shape)\n",
"print(\"Sampling rate:\", common_voice_train[rand_int][\"audio\"][\"sampling_rate\"])"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"id": "XobzwvyNZpxv"
},
"outputs": [],
"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"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
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},
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"outputId": "c89a5ac1-8410-492f-b83d-cefa901d7214"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ad819734e880445882cc1c22be3957e2",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"0ex [00:00, ?ex/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
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"0ex [00:00, ?ex/s]"
]
},
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}
],
"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)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Hu8imi4QZx3f"
},
"source": [
"Training"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"id": "rAYCcrJFZubm"
},
"outputs": [],
"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"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"id": "k05sM3rsZzGS"
},
"outputs": [],
"source": [
"data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"id": "T1zgf2ZKZ1et",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 49,
"referenced_widgets": [
"2a357b306c754f31b7fb251eb3cd2230",
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]
},
"outputId": "21e9d338-01a2-4ca3-f610-547b78be4027"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2a357b306c754f31b7fb251eb3cd2230",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/1.90k [00:00, ?B/s]"
]
},
"metadata": {}
}
],
"source": [
"wer_metric = load_metric(\"wer\")"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"id": "2J_feilIZ3Jf"
},
"outputs": [],
"source": [
"def compute_metrics(pred):\n",
" pred_logits = pred.predictions\n",
" pred_ids = np.argmax(pred_logits, axis=-1)\n",
"\n",
" pred.label_ids[pred.label_ids == -100] = processor.tokenizer.pad_token_id\n",
"\n",
" pred_str = processor.batch_decode(pred_ids)\n",
" # we do not want to group tokens when computing the metrics\n",
" label_str = processor.batch_decode(pred.label_ids, group_tokens=False)\n",
"\n",
" wer = wer_metric.compute(predictions=pred_str, references=label_str)\n",
"\n",
" return {\"wer\": wer}"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 192,
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},
"outputs": [
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a2bdc53c176e4e93a787e285c9c31d00",
"version_minor": 0,
"version_major": 2
},
"text/plain": [
"Downloading: 0%| | 0.00/1.53k [00:00, ?B/s]"
]
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "61d895147a8846fd9cd93ab6b7c70efa",
"version_minor": 0,
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},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Some weights of the model checkpoint at facebook/wav2vec2-xls-r-300m were not used when initializing Wav2Vec2ForCTC: ['quantizer.weight_proj.bias', 'project_q.bias', 'quantizer.weight_proj.weight', 'quantizer.codevectors', 'project_q.weight', 'project_hid.weight', 'project_hid.bias']\n",
"- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
"- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
"Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-300m and are newly initialized: ['lm_head.bias', 'lm_head.weight']\n",
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
]
}
],
"source": [
"from transformers import Wav2Vec2ForCTC\n",
"\n",
"model = Wav2Vec2ForCTC.from_pretrained(\n",
" \"facebook/wav2vec2-xls-r-300m\", \n",
" attention_dropout=0.05,\n",
" hidden_dropout=0.04,\n",
" feat_proj_dropout=0.0,\n",
" mask_time_prob=0.15,\n",
" layerdrop=0.02,\n",
" ctc_loss_reduction=\"mean\", \n",
" pad_token_id=processor.tokenizer.pad_token_id,\n",
" vocab_size=len(processor.tokenizer),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "h7MYlVI1Z-w8",
"outputId": "57cdf479-6576-4bca-d64b-4c3bca783e86"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1703: FutureWarning: The method `freeze_feature_extractor` is deprecated and will be removed in Transformers v5.Please use the equivalent `freeze_feature_encoder` method instead.\n",
" FutureWarning,\n"
]
}
],
"source": [
"model.freeze_feature_extractor()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"id": "DapYDcW4Z_Z0"
},
"outputs": [],
"source": [
"from transformers import TrainingArguments\n",
"\n",
"training_args = TrainingArguments(\n",
" output_dir=repo_name,\n",
" group_by_length=True,\n",
" per_device_train_batch_size=16,\n",
" gradient_accumulation_steps=2,\n",
" evaluation_strategy=\"steps\",\n",
" num_train_epochs=50,\n",
" gradient_checkpointing=True,\n",
" fp16=True,\n",
" save_steps=200,\n",
" eval_steps=200,\n",
" logging_steps=200,\n",
" learning_rate=0.00024,\n",
" warmup_steps=1800,\n",
" save_total_limit=2,\n",
" push_to_hub=True,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "jHiXuohDaD_5",
"outputId": "38740e1e-42e6-4800-9409-bb1ff99db2e3"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/content/wav2vec2-large-xls-r-300m-hi-wx1 is already a clone of https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1. Make sure you pull the latest changes with `repo.git_pull()`.\n",
"Using amp half precision backend\n"
]
}
],
"source": [
"from transformers import Trainer\n",
"\n",
"trainer = Trainer(\n",
" model=model,\n",
" data_collator=data_collator,\n",
" args=training_args,\n",
" compute_metrics=compute_metrics,\n",
" train_dataset=common_voice_train,\n",
" eval_dataset=common_voice_test,\n",
" tokenizer=processor.feature_extractor,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "27TZ79d_aIgO",
"outputId": "8f6a0a54-7bb2-4858-926f-aad3d23a41e9"
},
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
"/usr/local/lib/python3.7/dist-packages/transformers/optimization.py:309: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use thePyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
" FutureWarning,\n",
"***** Running training *****\n",
" Num examples = 4711\n",
" Num Epochs = 50\n",
" Instantaneous batch size per device = 16\n",
" Total train batch size (w. parallel, distributed & accumulation) = 32\n",
" Gradient Accumulation steps = 2\n",
" Total optimization steps = 7350\n"
]
},
{
"output_type": "display_data",
"data": {
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" \n",
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" \n",
" 6200 | \n",
" 0.086200 | \n",
" 0.649730 | \n",
" 0.325551 | \n",
"
\n",
" \n",
" 6400 | \n",
" 0.084800 | \n",
" 0.659933 | \n",
" 0.322587 | \n",
"
\n",
" \n",
" 6600 | \n",
" 0.079300 | \n",
" 0.662482 | \n",
" 0.323204 | \n",
"
\n",
" \n",
" 6800 | \n",
" 0.076000 | \n",
" 0.646304 | \n",
" 0.318634 | \n",
"
\n",
" \n",
" 7000 | \n",
" 0.074900 | \n",
" 0.655935 | \n",
" 0.322463 | \n",
"
\n",
" \n",
" 7200 | \n",
" 0.066300 | \n",
" 0.655239 | \n",
" 0.319993 | \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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/preprocessor_config.json\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600] 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 = 2095\n",
" Batch size = 8\n",
"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/pytorch_model.bin\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/preprocessor_config.json\n",
"Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800] 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"
]
},
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"Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1\n",
"Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/config.json\n",
"Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/pytorch_model.bin\n",
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"To https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1\n",
" e0cc599..26465e2 main -> 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': 'hi'}}\n",
"To https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1\n",
" 26465e2..a742827 main -> main\n",
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