{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YELVqGxMxnbG", "outputId": "a82687bb-f883-4e7b-a0c2-efb25ec5501b" }, "outputs": [], "source": [ "gpu_info = !nvidia-smi\n", "gpu_info = '\\n'.join(gpu_info)\n", "if gpu_info.find('failed') >= 0:\n", " print('Not connected to a GPU')\n", "else:\n", " print(gpu_info)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/workspace/sr\n" ] }, { "data": { "text/plain": [ "'/workspace/sr'" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%cd ~/sr\n", "%pwd" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 123, "referenced_widgets": [ "ce7c0523fe0945259eff9020e573a218", "2928d41f4f264ca0b9a31118462c0602", "2710004a535a4300b89f9f588c0e33e7", "95c3dfbff82641efbc32cdf38c3af315", "e75a354f58414a2aba65ac5f96f794d5", "498e0d2721e94804981d2caf9a14e998", "a8acab811f1a4c4480d2fbedecb3ef2d", "3e21794aba48497ab840c5076b766779", "15dce6e6c76b4b338dc8aa6fa70a68fb", "9d8cf219056e480f90b37b862a884f7f", "efc1548fb11249f1b6abf558feb70fdf", "139cb79e652741fb9800938f513a64ee", "132bece034d7436a92131a2d7c5447dd", "f09ffab604c84d10bc8f8a276fc56db8", "789237e5c6f844aaa461002dd4ff81a7", "bc7e8da097354af69a9eb31184b10cd9", "766028d8d74845c29e061423adafcc2f", "0b503fa95f214ca9a4a4f52ca6cf39ea", "01940c92e2124694a353fbe9daa3f519", "906ac30b1a53494292d5464776d4185d", "27192257c291482c9f45352a099fd293", "778e27b2713440a7a0f57b48ce98cac5", "8a02fd0543a04de680b0570df49c4ec7", "7aca3591dbd148e1bf684305f5898e9f", "37786f2415c54cf1a3feb36f51b1a9a1", "32decdfe9bce4359bee27513e12caae4", "af0431f7b5bb4c959c298136a2666c94", "14fb1d361cf04ceb82dc916d3ac62e58", "d0e7bdb7003845f18c57fa102c3d39ff", "dd05c4ec056448eebbd698715e4f206f", "45b52b113a404da9b395b816309cd48e", "99f1c52fc3294096a6614ed8cb0f8678", "3f0a938c876244dab220a0692240c68c", "df0a58bd514d4adb96eefa9c2e348e68", "5f9c66c0890c4732a01e25a3617d677f", "f83bdd44d071406490e036d64af71f86", "b7825d5c508e406da79df3c8d5bbf644", "6eefb11b33e144a8ba2776b450584d67", "910b0c36ffac45a39690e7da4b7bdd30", "f5b86244d5cd4651ab2c7849c3ef40b7", "fffa8820a0b3493cab82c939169016c7", "c01ad658495d499fb1f77f1f6e88091e", "6416eed0c2a24d11a54f99e217b1246b", "ddb765d3e944448ead769abd536452d3", "74222e06c53f46a9a4454214e7fc515b", "24da28b982fe4de5b11997146dc8ef5d", "f1a004bbcfe84b2da8bb9ab33d397de5", "0320e7bb34ab4273ae088c82df4fee0f", "9000f234d4c14beb87d4e82879b858df", "100cee605ec44cf5993d404b9be1ff61", "3b02e2b26f6446fb8ffb8357ff785b65", "c5991408225c4b3cb1f8dd069e947057", "5743625f77ca43779b8f971952e00f5d", "da885d5a5ef84747b9629690f35ecdc9", "10fa9c68afa245a4950e41df9e8c1578", "3bb6ab80915c46e09b42dcb87342959d", "169dcfbe96b544f0a4cf818249174fcb", "3d9b6280f5a249408192664ef7d81c59", "f4be19b71d7442199eda374c4e538009", "3995d68b7cb144549384cdf303f39f64", "be80480c4af1425299ad90f3bf699e60", "0d02bb1653904c8fb4f6a64c8676d721", "7a49ab8162374715ae5c639e9809835d", "49d7f826750f4a66b7bbe03a4afd5de0", "35c17be43018490c9667e8742a5538a5", "8f47611f826b493f9c8da960d5dca80f" ] }, "id": "2MMXcWFFgCXU", "outputId": "f12100b6-e3b1-4b8d-e4c5-85c8343f1e8a" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/sr/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8)\n", "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/sr/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8)\n" ] } ], "source": [ "from datasets import load_dataset, load_metric, Audio\n", "\n", "common_voice_train = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"sr\", split=\"train+validation\", use_auth_token=True)\n", "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_8_0\", \"sr\", split=\"test\", use_auth_token=True)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "bGF9rR_9oX71", "outputId": "363b62cd-c825-49d1-d1cd-f6fa20742dba" }, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "common_voice_train.cleanup_cache_files()\n", "common_voice_test.cleanup_cache_files()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "id": "kbyq6lDgQc2a" }, "outputs": [], "source": [ "common_voice_train = common_voice_train.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])\n", "common_voice_test = common_voice_test.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "72737oog2F6U" }, "outputs": [], "source": [ "from datasets import ClassLabel\n", "import random\n", "import pandas as pd\n", "from IPython.display import display, HTML\n", "\n", "def show_random_elements(dataset, num_examples=10):\n", " assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n", " picks = []\n", " for _ in range(num_examples):\n", " pick = random.randint(0, len(dataset)-1)\n", " while pick in picks:\n", " pick = random.randint(0, len(dataset)-1)\n", " picks.append(pick)\n", " \n", " df = pd.DataFrame(dataset[picks])\n", " display(HTML(df.to_html()))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 363 }, "id": "K_JUmf3G3b9S", "outputId": "1c220991-320f-470b-b334-992ac78c411e" }, "outputs": [ { "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
0Једна од њих.
1Изгледи земље су према рејтингу стабилни.
2Па, реци ми!
3Е па, немојте.
4Шта ако се прогноза покаже погрешном?
5Ја мислим овако.
6Да вам кажем?
7Док сам жив.
8Земља наша има дакле врло дуготрајну историју
9Много горе ствари.
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_random_elements(common_voice_train.remove_columns([\"path\", \"audio\"]), num_examples=10)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "id": "ZcVsD0ETElrR" }, "outputs": [], "source": [ "import re\n", "chars_to_remove_regex = '[\\,\\?\\.\\!\\-\\;\\:\\/\\\"\\“\\„\\%\\”\\�\\–\\'\\`\\«\\»\\—\\’\\…\\³cejy]'\n", "\n", "\n", "CHARS = {\n", " 'ü': 'ue',\n", " 'ö': 'oe',\n", " 'ï': 'i',\n", " 'ë': 'e',\n", " 'ã': 'a',\n", " 'à': 'á',\n", " 'ø': 'o',\n", " 'è': 'é',\n", " 'ê': 'é',\n", " 'å': 'ó',\n", " 'î': 'i',\n", " 'ñ': 'ň',\n", " 'ç': 's',\n", " 'þ': 't',\n", " 'ß': 'ss',\n", " 'ę': 'en',\n", " 'ą': 'an',\n", " 'æ': 'ae',\n", " }\n", "\n", "def replace_chars(sentence):\n", " result = ''\n", " for ch in sentence:\n", " new = CHARS[ch] if ch in CHARS else ch\n", " result += new\n", "\n", " return result\n", "\n", "\n", "def remove_special_characters(batch):\n", " batch[\"sentence\"] = re.sub(chars_to_remove_regex, ' ', batch[\"sentence\"]).lower()\n", " batch[\"sentence\"] = replace_chars(batch['sentence'])\n", " batch[\"sentence\"] = \" \".join([char for char in batch[\"sentence\"].split(\" \") if char != \"\"])\n", " return batch\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 395, "referenced_widgets": [ "f9a0f686f75749f6b403472ed4e23c41", "4a2bf06b19f4463187d55018d95816e1", "e9f7b6f84f1444719a09b4b8596ae0f4", "443b7b937b124b8fb76299c95ae0427c", "c2ad79e0a9ea4c9386103888d5babdfa", "963f4075f46540a9870dc2806216af9e", "7db6c36db0d5499290b09a0f01451f2c", "8f0c1ea28c274345a5748af60f4d55f1", "b071746dc76d4673a47b298a8bc54562", "f9490b9aa92e4d909605d93209a8f746", "81b75ff4e800472c8e3fa5516dbdda01" ] }, "id": "6falIJSBED65", "outputId": "17bdc176-6574-4c95-8ee8-028171eb91a6" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "328ae6e8c61b495faadceb694a263221", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0ex [00:00, ?ex/s]" ] }, "metadata": {}, "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
0међутим није баш све тако лако
1и још један
2у београду је бојкот
3у оба домена регион има још пуно резерви
4ко сте ви
5веома реалистични
6то сам хтео
7а у овој
8а то не
9молим да седнем
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_random_elements(common_voice_train.map(remove_special_characters).remove_columns([\"path\", \"audio\"]), num_examples=10)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 87, "referenced_widgets": [ "0e458554a0bc49989a29d142143c3d75", "037bba1874d949e78e5c119de5c49346", "456b8b329b3146b6ab5c62fa95b09bca", "b475c78857b94d1682ac8a05f721d9e1", "652001e3c17747019f9c586a33ac5f51", "f9514e38321144ceae29a5d66055c3eb", "85a8171857e54c9eab29e6ba66a6f573", "d7174f55c32b48c4be4ef195745ffcce", "75020f745e3448b588edba867ff5f80d", "a5370b4c03e644b780cc95f27c131677", "3015c569defd4355a7a41cd196178c30" ] }, "id": "XIHocAuTQbBR", "outputId": "a12a767f-c745-483a-e34f-c166cbc449b5" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Loading cached processed dataset at /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/sr/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8/cache-2b2b6581a24f7582.arrow\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5bb954f08f21477c9650b0f5910aa13e", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0ex [00:00, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "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": 11, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 363 }, "id": "RBDRAAYxRE6n", "outputId": "51d5ce04-ddab-4696-d220-4de82e45f2db" }, "outputs": [ { "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
0далеко од мене
1што није дошао
2више од мене
3не знам какав
4у томе је разлика
5не знам за то
6у таквом једном
7гуча је дивна
8у годину дана
9ја сам го
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_random_elements(common_voice_train.remove_columns([\"path\",\"audio\"]))" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "id": "LwCshNbbeRZR" }, "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": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "f5973eb0a46649d687b6b39f9eb6ffa8", "aa8f567a963e45a6aec3c45b115237b0", "475d142e1b534033a1eccd883071eead", "3eb9f71f91e64ef9aa52f09b653dbf1d", "acf1dc77638041d5ae9c44f8bfc6f4bd", "ae7e4f8ea7924fea87e5992f7f432b06", "e2bae0a5e3064e30a38577e7eb42c80d", "8f8867a2bae648d49250492abf91bfdc", "a595885e78b84450b737b75f30240241", "627328b576ba467abe48eb9e560eaefe", "f59165b748264c289de5a31fd12d4346", "547084e427ac480eb4df3d9e2b74c2a7", "73168e226d4740a4b8cebb119b262f73", "d105bf5fa4b941ae8e04c38094d46b30", "26fc7d20bc344ee4b73feb32be518235", "5a570f67cfeb4a079c1c7061a1be2090", "aaa5b759b4264a079b7f29168e4e6154", "8cc5dce835864f12bf07206068c76ed9", "68b2db3dd6b8448385258e8491e3764b", "e325fed7d2e64a3ca96ac7a7660786d5", "6e55def79a344b62a7f5bcbf3be3a816", "5c5ea9c8e4974b4db55eee20726f9aa6" ] }, "id": "_m6uUjjcfbjH", "outputId": "edb40365-d4aa-4ef1-c8d8-870e6a5d9e6e" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4a202c6ede9941ae932b075489e3da8f", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1 [00:00\n", " \n", " Your browser does not support the audio element.\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "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": 29, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1Po2g7YPuRTx", "outputId": "97d86ad2-b5a1-444f-8c7d-f5d807529f90" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Target text: овде код мене\n", "Input array shape: (40320,)\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": 30, "metadata": { "id": "eJY7I0XAwe9p" }, "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": 31, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "c47ea368dd08403aa09b2bafdbb4b580", "e77cf973d5824ae7b89bafd814805c2a", "071b7647e1fe49609a48e4281a9efd0f", "c97c00fcf2e64f18b637337f9244d748", "9ca82fa27d1043e9ac9f10301e0b33bc", "cc6c7e9931c140db8ba7a977c4461ce5", "d207784bda7e4dd8858170f470ae2833", "0800fef7de6e45d380873f974882d67e", "926440595aa44c698588e02b86eb8c4c", "ea2806c776384f1a90e36b72c2c17a44", "6b72385c07134782995fcd76e675da7c", "3653b92c9f2a408eac253e1d5153daf4", "73ffd9b8166c4ec78ff2b62d17690327", "6b133a1e11e44f68846ff931446559cf", "7c98818547c84af7ba9284bc20101691", "41b501a16b2a4f709197af5cdd5227cb", "3b4fbe2916894e48b8f93ca63e203aca", "c002386685c0413d8181b054d3f9d49f", "cfb70829b5e1461abcb01872b74a194c", "ed943db2b5274022a606ce4103d54425", "cfb242eb549c4e66afcedefb575b4e38", "a0313055d29f4a60837e59ac4d8a3870" ] }, "id": "-np9xYK-wl8q", "outputId": "573f6f67-e5b2-4977-a564-3919e7903592" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3afda27b68d64144ad050f014df200ff", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0ex [00:00, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ea1692f0699146b6842af01b2ac893ae", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0ex [00:00, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "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": "code", "execution_count": 32, "metadata": { "id": "tdHfbUJ_09iA" }, "outputs": [], "source": [ "#max_input_length_in_sec = 5.0\n", "#common_voice_train = common_voice_train.filter(lambda x: x < max_input_length_in_sec * processor.feature_extractor.sampling_rate, input_columns=[\"input_length\"])" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "id": "tborvC9hx88e" }, "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": 34, "metadata": { "id": "lbQf5GuZyQ4_" }, "outputs": [], "source": [ "data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "id": "9Xsux2gmyXso" }, "outputs": [], "source": [ "wer_metric = load_metric(\"wer\")\n", "cer_metric = load_metric(\"cer\")\n", "metrics = [wer_metric, cer_metric]" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "id": "1XZ-kjweyTy_" }, "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", " cer = cer_metric.compute(predictions=pred_str, references=label_str)\n", "\n", " return {\"wer\": wer, \"cer\": cer}" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "e7cqAWIayn6w", "outputId": "7a7ef020-bc8f-41e2-846c-645be598312e" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Some weights of the model checkpoint at facebook/wav2vec2-xls-r-300m were not used when initializing Wav2Vec2ForCTC: ['project_q.bias', 'project_q.weight', 'project_hid.weight', 'quantizer.codevectors', 'quantizer.weight_proj.bias', 'project_hid.bias', 'quantizer.weight_proj.weight']\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", " #\"comodoro/wav2vec2-xls-r-300m-west-slavic-cv8\", \n", " \"facebook/wav2vec2-xls-r-300m\", \n", " attention_dropout=0.2,\n", " hidden_dropout=0.2,\n", " feat_proj_dropout=0.1,\n", " mask_time_prob=0.5,\n", " layerdrop=0.4,\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": 38, "metadata": { "id": "oGI8zObtZ3V0" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/workspace/.local/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1700: 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", " warnings.warn(\n" ] } ], "source": [ "model.freeze_feature_extractor()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "id": "KbeKSV7uzGPP" }, "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=1,\n", " eval_accumulation_steps=1,\n", " evaluation_strategy=\"steps\",\n", " num_train_epochs=800,\n", " gradient_checkpointing=True,\n", " fp16=True,\n", " save_steps=1200,\n", " eval_steps=1200,\n", " logging_steps=1200,\n", " learning_rate=1e-4,\n", " warmup_steps=300,\n", " save_total_limit=2,\n", " report_to=\"tensorboard\"\n", ")" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "rY7vBmFCPFgC", "outputId": "a180bf3f-f798-4947-ff58-207d7aaab695" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "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": 41, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 312 }, "id": "9fRr9TG5pGBl", "outputId": "8bdf1d11-bca1-46af-db67-518f85586f7a" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "/workspace/.local/lib/python3.8/site-packages/transformers/optimization.py:306: 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", " warnings.warn(\n", "***** Running training *****\n", " Num examples = 1278\n", " Num Epochs = 800\n", " Instantaneous batch size per device = 16\n", " Total train batch size (w. parallel, distributed & accumulation) = 16\n", " Gradient Accumulation steps = 1\n", " Total optimization steps = 64000\n" ] }, { "data": { "text/html": [ "\n", "
\n", " \n", " \n", " [64000/64000 10:50:15, Epoch 800/800]\n", "
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StepTraining LossValidation LossWerCer
12005.6536002.9743821.0000001.000000
24002.7935001.6612990.8997670.466951
36001.6538000.9248290.6918410.269857
48001.2446000.9150670.6452210.239812
60001.0766000.9109710.5995340.220693
72000.9548001.0272550.5920750.214902
84000.8919000.9929380.5645690.211734
96000.8185001.0850030.5482520.206927
108000.7692001.1001090.5393940.205506
120000.7249001.1018050.5379950.195783
132000.6786001.1343820.5114220.194144
144000.6432001.1516330.5053610.190539
156000.6009001.3149000.5324010.199060
168000.5773001.2467990.5123540.190320
180000.5590001.2186380.4955710.192177
192000.5298001.4483360.5333330.208456
204000.5136001.2871330.4801860.184639
216000.4824001.2891300.4974360.188463
228000.4669001.3282680.4941720.187807
240000.4511001.4502340.5002330.199388
252000.4337001.4713710.5034970.191085
264000.4221001.4971450.5123540.196220
276000.3994001.4473120.5006990.191959
288000.3892001.3903540.4937060.188681
300000.3730001.4970820.4946390.190211
312000.3657001.4207560.4899770.182126
324000.3559001.4647840.4895100.183546
336000.3476001.4848200.4946390.182891
348000.3276001.5597380.4979020.187261
360000.3193001.7329340.5039630.197968
372000.3078001.6378740.4937060.188244
384000.3058001.5878500.4941720.192068
396000.2987001.5589590.4811190.184639
408000.2931001.6001470.4825170.184857
420000.2760001.7387650.4941720.191850
432000.2702001.7037140.4839160.186605
444000.2619001.6704130.4755240.183983
456000.2620001.6041900.4750580.186496
468000.2528001.6401640.4820510.186496
480000.2442001.6693310.4885780.186168
492000.2440001.6203440.4764570.179176
504000.2388001.6829170.4829840.182782
516000.2362001.8100270.4927740.188791
528000.2224001.7746440.4932400.189883
540000.2218001.7752070.4946390.190102
552000.2201001.6775390.4787880.184420
564000.2147001.7085220.4843820.185076
576000.2103001.7624140.4848480.186387
588000.2101001.7212620.4783220.183546
600000.1983001.7452280.4848480.185622
612000.2015001.7524870.4871790.186933
624000.1969001.7442970.4843820.185185
636000.2043001.7302270.4825170.184748

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-1200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-1200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-1200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-1200/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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-2400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-2400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-2400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-2400/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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-3600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-3600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-3600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-3600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-1200] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "***** Running Evaluation *****\n", " Num examples = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-4800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-4800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-4800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-4800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-2400] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "***** Running Evaluation *****\n", " Num examples = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-6000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-6000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-6000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-6000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-3600] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "***** Running Evaluation *****\n", " Num examples = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-7200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-7200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-7200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-7200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-4800] due to args.save_total_limit\n", "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "***** Running Evaluation *****\n", " Num examples = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-8400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-8400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-8400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-8400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-9600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-9600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-9600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-9600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-7200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-10800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-10800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-10800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-10800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-8400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-12000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-12000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-12000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-12000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-9600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-13200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-13200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-13200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-13200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-10800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-14400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-14400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-14400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-14400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-12000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-15600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-15600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-15600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-15600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-13200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-16800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-16800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-16800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-16800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-14400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-18000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-18000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-18000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-18000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-15600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-19200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-19200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-19200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-19200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-16800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-20400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-20400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-20400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-20400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-18000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-21600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-21600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-21600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-21600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-19200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-22800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-22800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-22800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-22800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-20400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-24000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-24000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-24000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-24000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-21600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-25200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-25200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-25200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-25200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-22800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-26400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-26400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-26400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-26400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-24000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-27600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-27600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-27600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-27600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-25200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-28800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-28800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-28800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-28800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-26400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-30000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-30000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-30000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-30000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-27600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-31200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-31200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-31200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-31200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-28800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-32400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-32400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-32400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-32400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-30000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-33600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-33600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-33600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-33600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-31200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-34800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-34800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-34800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-34800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-32400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-36000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-36000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-36000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-36000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-33600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-37200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-37200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-37200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-37200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-34800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-38400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-38400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-38400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-38400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-36000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-39600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-39600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-39600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-39600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-37200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-40800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-40800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-40800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-40800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-38400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-42000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-42000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-42000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-42000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-39600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-43200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-43200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-43200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-43200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-40800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-44400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-44400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-44400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-44400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-42000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-45600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-45600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-45600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-45600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-43200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-46800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-46800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-46800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-46800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-44400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-48000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-48000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-48000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-48000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-45600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-49200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-49200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-49200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-49200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-46800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-50400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-50400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-50400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-50400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-48000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-51600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-51600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-51600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-51600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-49200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-52800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-52800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-52800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-52800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-50400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-54000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-54000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-54000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-54000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-51600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-55200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-55200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-55200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-55200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-52800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-56400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-56400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-56400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-56400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-54000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-57600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-57600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-57600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-57600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-55200] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-58800\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-58800/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-58800/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-58800/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-56400] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-60000\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-60000/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-60000/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-60000/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-57600] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-61200\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-61200/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-61200/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-61200/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-58800] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-62400\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-62400/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-62400/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-62400/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-60000] 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 = 598\n", " Batch size = 8\n", "Saving model checkpoint to wav2vec2-xls-r-300m-sr-cv8/checkpoint-63600\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-63600/config.json\n", "Model weights saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-63600/pytorch_model.bin\n", "Configuration saved in wav2vec2-xls-r-300m-sr-cv8/checkpoint-63600/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-xls-r-300m-sr-cv8/checkpoint-61200] 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" ] }, { "data": { "text/plain": [ "TrainOutput(global_step=64000, training_loss=0.5902130200862884, metrics={'train_runtime': 39016.0873, 'train_samples_per_second': 26.205, 'train_steps_per_second': 1.64, 'total_flos': 8.84302567787997e+19, 'train_loss': 0.5902130200862884, 'epoch': 800.0})" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trainer.train()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "#model.push_to_hub(clone_from=https://huggingface.co/comodoro/wav2vec2-xls-r-300m-west-slavic-cv8)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Configuration saved in ./config.json\n", "Model weights saved in ./pytorch_model.bin\n" ] } ], "source": [ "model.save_pretrained('.')" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Dropping the following result as it does not have all the necessary fields:\n", "{'dataset': {'name': 'common_voice', 'type': 'common_voice', 'args': 'sr'}}\n" ] } ], "source": [ "trainer.create_model_card()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "accelerator": "GPU", "colab": { "collapsed_sections": [], "machine_shape": "hm", "name": "Kopie sešitu \"Fine-Tune XLS-R on Common Voice.ipynb\"", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "01940c92e2124694a353fbe9daa3f519": { 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