diff --git "a/BRd2.ipynb" "b/BRd2.ipynb" new file mode 100644--- /dev/null +++ "b/BRd2.ipynb" @@ -0,0 +1,8816 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "pwqX3mdhXwx5", + "outputId": "5da02559-e3df-490b-904f-b2ddc51318f4" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Thu Feb 3 15:59:05 2022 \n", + "+-----------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 460.32.03 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 41C P0 27W / 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" + ] + } + ], + "source": [ + "!nvidia-smi" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "5SUbafEAX0CJ" + }, + "outputs": [], + "source": [ + "%%capture\n", + "!pip install datasets --upgrade\n", + "!pip install transformers\n", + "!pip install huggingface_hub\n", + "!pip install torchaudio\n", + "!pip install jiwer" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 388, + "referenced_widgets": [ + "39fadf84ded64e32ba0fae9ae504c740", + "9de0e393ab34480a98288edcb1e2de0e", + "d1a2d09016b546498efc9ec72d1c750f", + "b28a162884e54e8bad3261d753650a7c", + "fb2f749120094184980a564649ffdab0", + "38ebe9b067f847de90a07f39d0c3c98c", + "311b5be02a6b4201baa35709aef45223", + "17f0ef0c67a14224b950946bd883e3a4", + "de269eee29954bcd85dde11edabe32b3", + "d74b543cc1124939aeb0b5ec2cec49ca", + "061863ca9a264b3b97251f7d70ff355b", + "61ea9728aa804ccaa7b91c78152cd981", + "d754bf96725e499dbffedf6efd504ae6", + "76c674c0c3e84caf94146b63e3b00ffe", + "730588def524406fa728e7b793d03f5e", + "c6a91aa7ba934142bd5151caf7b7d95d", + "d9a76cd1b0ab4497a305f783b2809b27" + ] + }, + "id": "rWmcNVb2X7Hd", + "outputId": "65939f47-476f-4a76-c25f-cb25f7982478" + }, + "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" + ] + } + ], + "source": [ + "from huggingface_hub import notebook_login\n", + "\n", + "notebook_login()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3X_6k7imX9L8" + }, + "outputs": [], + "source": [ + "%%capture\n", + "!apt install git-lfs" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pP37N8UPYJ9K" + }, + "source": [ + "#Create Wav2Vec2CTCTokenizer" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 220, + "referenced_widgets": [ + "9d483e020adf4ee98d3eb93396fdf1e1", + "a3ca56298476482dadb68bb99523818a", + "4ece928827fe4eb5b4643fb54de870f1", + "4915b3156f374f329c9a5b19b428ddd9", + "8d5cfdd2fc1d4ba08cfbd78f9a412a82", + "b964d0c947cc483eb411b1fc381e872e", + 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+ " \n", + " 0\n", + " anvioù-bihan hag anv ar gwaz nevez.\n", + " \n", + " \n", + " 1\n", + " bremañ e pesketit.\n", + " \n", + " \n", + " 2\n", + " \"sec'hed he deus.\"\n", + " \n", + " \n", + " 3\n", + " Efed implij ar yezh gant ar strollegezhioù war ar mod ma vez gwelet o yezh gant ar vrezhonegerien, ha gant ar Vretoned na ouzont ket brezhoneg.\n", + " \n", + " \n", + " 4\n", + " \"Gwashoc'h c'hoazh !\"\n", + " \n", + " \n", + " 5\n", + " \"n'eus ket anv e taolfe e droad amañ.\"\n", + " \n", + " \n", + " 6\n", + " \"Kasit ac'hanon d'ar Mariott Hotel.\"\n", + " \n", + " \n", + " 7\n", + " Dale am bo.\n", + " \n", + " \n", + " 8\n", + " em glin.\n", + " \n", + " \n", + " 9\n", + " \"nevez-flamm eo va c'harr-tan.\"\n", + " \n", + " \n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "show_random_elements(common_voice_train.remove_columns([\"path\", \"audio\"]), num_examples=10)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "NRDcDNteYabw" + }, + "outputs": [], + "source": [ + "import re\n", + "chars_to_remove_regex = '[\\,\\?\\.\\!\\-\\;\\:\\\"\\“\\%\\‘\\”\\�\\'\\।\\&\\|\\’]'\n", + "\n", + "def remove_special_characters(batch):\n", + " batch[\"sentence\"] = re.sub(chars_to_remove_regex, '', batch[\"sentence\"]).lower()\n", + " return batch" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "365c3d771dde438fb07f2e34bd0728e7", + "a940dc3df1054f7086b78efe9f3cb717", + "f91dfcf5a8be4b0183cfba4a2afb1971", + "76669691c0ff4d41a6be5a6bdf9694eb", + "a014c5cf000441b28c49947f7ad67a3d", + "1e5b86384f914df09c93b93e13f5d22e", + "1db391d2b3bc4745a1641faf6234bd07", + "8e272e2631994480afcb6eb01cd5acf1", + "bf6dba4a758f4b4d8cf44bae5a5c581f", + "e449275721d9418283e0bf44ff0b94f6", + "aadda6e400d24235a4fb32eee0c43117", + "4d0e51bf8575476c993f9b2da19f76ae", + 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"metadata": {} + } + ], + "source": [ + "common_voice_train = common_voice_train.map(remove_special_characters)\n", + "common_voice_test = common_voice_test.map(remove_special_characters)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 363 + }, + "id": "5XHPLLvAYeMY", + "outputId": "628e508e-cfa7-49fe-cd29-6214f50f056d" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "\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", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sentence
0ya vat
1chwitellat a ra en ur labourat
2chwech kador vihan
3neus ket dour
4redek evit reiñ lusk dar yezh
5ober a ra penn mouzh
6… eo ma anv
7ma nhallez ket choari
8daou re zivaskell he deus an nadozaer
9ouzh peseurt tarzh roadennoù hocʼh eus cʼhoant da gevreañ
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "show_random_elements(common_voice_train.remove_columns([\"path\",\"audio\"]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "z0UilCejYk66" + }, + "outputs": [], + "source": [ + "def extract_all_chars(batch):\n", + " all_text = \" \".join(batch[\"sentence\"])\n", + " vocab = list(set(all_text))\n", + " return {\"vocab\": [vocab], \"all_text\": [all_text]}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "4c78d99ed83a40589f9952064a73e053", + "c1772cdef1aa4caea99dbd5d72be3fee", + "49d1600d176a4c958af0e78a10bebe1f", + "cde1cdab5347484a99fea7d4615bc2fe", + "06b683b8d8254015817bc226521937ed", + "05554d7ec68a4c5c9e4fb34ac7a80033", + "5b420fc5d442428f929fc53217568d2e", + "dfd016aaaa064cdea45bcf182a4240fd", + "69ee571a17c6470b8e29ac161d96b36c", + 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"text/plain": [ + "'https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-br-d2/commit/b65d7219f731de2203eecac17fbd086cd8fae554'" + ] + }, + "metadata": {}, + "execution_count": 24 + } + ], + "source": [ + "tokenizer.push_to_hub(repo_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9vYsH0F1ZWTa" + }, + "source": [ + "#Create Wav2Vec2FeatureExtractor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "y_rImGQgZTOf" + }, + "outputs": [], + "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)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zo4VRjMpZalf" + }, + "outputs": [], + "source": [ + "from transformers import Wav2Vec2Processor\n", + "\n", + "processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 36 + }, + "id": "C2VeeMJXZcPc", + "outputId": "bc91f091-564a-422e-a8b0-7185dabc7e25" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'cv-corpus-8.0-2022-01-19/br/clips/common_voice_br_17333681.mp3'" + ] + }, + "metadata": {}, + "execution_count": 27 + } + ], + "source": [ + "common_voice_train[0][\"path\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "0VJbeciEZd53", + "outputId": "29926813-4b44-42c1-bd1e-43fa0c52cc30" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "{'array': array([ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " -4.9769878e-05, -3.3795834e-05, 5.3048134e-06], dtype=float32),\n", + " 'path': 'cv-corpus-8.0-2022-01-19/br/clips/common_voice_br_17333681.mp3',\n", + " 'sampling_rate': 48000}" + ] + }, + "metadata": {}, + "execution_count": 28 + } + ], + "source": [ + "common_voice_train[0][\"audio\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "-hNJcREpZfiR" + }, + "outputs": [], + "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))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "6HR62lRYZil3", + "outputId": "d681bad5-2dba-42a9-e622-04be1c380017" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "{'array': array([ 0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n", + " -3.7581591e-05, -5.6451900e-05, -4.3939723e-05], dtype=float32),\n", + " 'path': 'cv-corpus-8.0-2022-01-19/br/clips/common_voice_br_17333681.mp3',\n", + " 'sampling_rate': 16000}" + ] + }, + "metadata": {}, + "execution_count": 30 + } + ], + "source": [ + "common_voice_train[0][\"audio\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 93 + }, + "id": "olI1RRluZkYk", + "outputId": "bcd6c3fa-5f2b-4eaa-f7fe-39d6f9776775" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "dre ma faot\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 31 + } + ], + "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": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "EE5jG9PVZmWU", + "outputId": "fb86bfb5-c22e-4fb0-c4d8-f31510220b5f" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Target text: mat eo an holl\n", + "Input array shape: (29184,)\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": null, + "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": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "fa0cb6eb3e0047a6b521c8ebc85ebf0a", + "64f4d8548b454fc49a051f1cc17ad215", + "0857a6d453e747dc9219510c0e937111", + "cd8e34ed04da43de8784956bbddb214a", + "2fbf28b3f44e48718f017e75f78159aa", + "cd041625b75c4e2ebefbaa4955ea2f4d", + "41b5421e7ded4bc68413021b49e3f457", + "e3fc96cd278c43a48edf1b53e661b88d", + "366b875600424fef8d5eca183f5c5db5", + "dfb75a16170b4fb6b8ec3695b5828d69", + "92415e896e8245fc954bc2a70c2135af", + "a019444372314e1c9ca2752a5f90b6d8", + "b60e91863d6549eba86f28bda9731324", + "809899a8619046678dac9d2e833f6916", + "9ed9d4eedd7f426bb5e4cab2d42cf9c8", + "71cadab4424048dbb783297aaaf2c943", + "00b201849a9e413b9801d9c44bc5519b", + "8ba251908727417e88b842f0db502bf9", + "be80effd3dbf4e9693a358937338f283", + "e8fa7ab09d7a4b0eab153734c6f6e576", + "1bf12ebcfaf64341a1331b5bc4fbf8d6", + "0899a2c108c24ac1a3d1d7818d462e49" + ] + }, + "id": "A7gT1EQMZsvz", + "outputId": "c839172b-4ba3-461a-ba41-267ec849577c" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fa0cb6eb3e0047a6b521c8ebc85ebf0a", + "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": "a019444372314e1c9ca2752a5f90b6d8", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + } + ], + "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": null, + "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": null, + "metadata": { + "id": "k05sM3rsZzGS" + }, + "outputs": [], + "source": [ + "data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "b1f9950cc1014614a4bc26999488c80b", + "f8d25a96c73c4efda52f34056d43a30e", + "dda2dbd4792947709d4cdbdd94458a79", + "dff44a4077964988adafdb6dc86f3769", + "bb131a315ed04f75a99ecd94c283ee3e", + "0d7df4119b8a42ea940de05376c04ff1", + "533265e47dd54713bfe3693e6911fabb", + "6697485c34b146248998fb161f6caf66", + "e864b6e21b2e4949a67ae1319210b6e5", + "b1577fc611cd4f56995ca186dcc40be0", + "5e8b10bdaa124fc0bbd3ea8f47f84248" + ] + }, + "id": "T1zgf2ZKZ1et", + "outputId": "29adbbf5-bb17-45b0-b1d2-893d6b51f4c3" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b1f9950cc1014614a4bc26999488c80b", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/1.90k [00:00\n", + " \n", + " \n", + " [ 2276/29600 2:50:44 < 34:11:38, 0.22 it/s, Epoch 15.37/200]\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \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", + " \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
10013.2579005.4250551.000000
2003.8341003.2413491.000000
3003.0659003.0152891.000000
4002.5976001.6643360.965399
5001.3209001.1996320.830530
6001.0514001.0586050.774517
7000.8452001.0553700.763812
8000.7434001.0390970.730071
9000.6983000.9416230.662302
10000.5890000.9367970.654464
11000.5113000.9789240.643567
12000.5014000.9714630.617282
13000.4272000.9449810.616517
14000.3762000.9447480.630185
15000.3793001.0065780.598738
16000.3683000.9236940.600746
17000.3197001.0511320.622252
18000.3181001.0268350.605429
19000.2903001.0645260.581438
20000.2812001.0318650.585357
21000.2805001.0359070.588415
22000.2503001.0327330.572357

" + ], + "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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-100\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-100/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-100/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-100/preprocessor_config.json\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-200/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-300\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-300/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-300/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-300/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-100] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-500\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-500/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-500/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-500/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-300] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-700\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-700/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-700/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-700/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-500] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-900\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-900/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-900/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-900/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-700] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1100\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1100/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1100/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1100/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-900] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1300\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1300/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1300/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1300/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-1100] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1500\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1500/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1500/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1500/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-1300] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1700\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1700/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1700/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1700/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-1500] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-1900\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1900/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1900/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-1900/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-1700] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-2000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-2100\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2100/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2100/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2100/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-1900] 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 = 2147\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-br-d2/checkpoint-2200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-br-d2/checkpoint-2200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-br-d2/checkpoint-2000] due to 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