diff --git "a/Hindi_wx1.ipynb" "b/Hindi_wx1.ipynb" new file mode 100644--- /dev/null +++ "b/Hindi_wx1.ipynb" @@ -0,0 +1,13537 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "pwqX3mdhXwx5", + "outputId": "b6f9ab33-a29f-4872-e541-92bd635714b8" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Mon Feb 7 13:07:37 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 45C P0 29W / 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": 8, + "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": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 388, + "referenced_widgets": [ + "c4bee46bce3148d9b88f713c4f0af8d7", + "70331383e3244b2eb034205e3f9e7887", + "eef579b138e44e8c911e080b606d8a10", + "aa28b2c596e94431b01c76772ad4c596", + "103318ac50844371b0d1f92636bca013", + "522c16052a6f41028bb38c2ee2cc0b25", + "717af7ff1f8645e289d39050d1c23866", + "babe01ea1f984685ae790648d8781d81", + "c58e9cd5b2194818a37e7d576c829594", + "4e1d65e11d5a4d5c940d104c3da4de4c", + "1038dfb9e75d455eabb2aae79a69b538", + "80766ad3a7d644b9a85983ec1bfa9dce", + "53e3ad04f3d349a29b263c5770e14f65", + "c5f7217b92e54e9cad9bfac85ebc61e7", + "e4fce096c83c4dd7a995c9a6a094d32e", + "2797eb9aa17245ca9d9d1e88a41754cf", + "c4de7475a996431692b1e47282cc8d0e" + ] + }, + "id": "rWmcNVb2X7Hd", + "outputId": "fbe7cf04-c40c-49d9-c2db-6e67ce819130" + }, + "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": 10, + "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": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 220, + "referenced_widgets": [ + "f473e5682cd34e3aaa2652fedca1a898", + "2b4ab98e182c4fe78b6c348fd852c1f9", + "03fc8879766f45cdba73cc23d78da6e2", + "29eb68e15ef846a6aae2b703d474b8c6", + "2cbbf8a6a53047399bb02c0d32260105", + "4753adb91e814e858209de278f17086b", + 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+ " \n", + " 0\n", + " सचिन तेंडुलकर: श्रद्धालुओं के बीच भगवान\n", + " \n", + " \n", + " 1\n", + " बेली फैट कम करने के लिए अपना सकते हैं ये घरेलू उपाय\n", + " \n", + " \n", + " 2\n", + " वह तुम हो।\n", + " \n", + " \n", + " 3\n", + " नीतीश कुमार एक बार फिर चुने गए जेडीयू के राष्ट्रीय अध्यक्ष\n", + " \n", + " \n", + " 4\n", + " लोहा सोने से ज़्यादा उपयोगी होता है।\n", + " \n", + " \n", + " 5\n", + " मोदी ने कालेधन के मुद्दे को अंतरराष्ट्रीय रंग दिया: रविशंकर प्रसाद\n", + " \n", + " \n", + " 6\n", + " यूनिफॉर्म सिविल कोड से जुड़ी याचिकाओं पर सुनवाई नवंबर त��� टली\n", + " \n", + " \n", + " 7\n", + " भारत में चलता है ट्रंप का नाम, रियल्टी कारोबार में है दखल\n", + " \n", + " \n", + " 8\n", + " उसे कुछ भी याद नहीं।\n", + " \n", + " \n", + " 9\n", + " रजनीकांत के साथ की गई ये गलती चुनाव अधिकारियों पर पड़ सकती है भारी\n", + " \n", + " \n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "show_random_elements(common_voice_train.remove_columns([\"path\", 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"version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "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": 17, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 363 + }, + "id": "5XHPLLvAYeMY", + "outputId": "1573ff34-ce67-4f4b-8b9c-ae509290180d" + }, + "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", + " 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sentence
0वह असली सोना है
1उन दिनों में सफ़र करना बहुत मुश्किल हुआ करता था
2मैं पैरिस जाकर आर्ट पढ़ना चाहती हूँ
3तुम ताओवादी हो
4वह अमीर है मगर उसका बड़ा भाई गरीब है
5उसने अपने बेटे के लिए बड़ी जायदाद छोड़ी
6टॉम का क्या मतलब था
7बिहार में बारिश जारी पारा लुढ़का
8अरे यह क्या है
9क्या मैं काॅफी बना दूं
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "show_random_elements(common_voice_train.remove_columns([\"path\",\"audio\"]))" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "id": "fO2xzS9aYgwV" + }, + "outputs": [], + "source": [ + "def replace_english_letters(batch):\n", + " batch[\"sentence\"] = re.sub('[a-z]', '', batch[\"sentence\"])\n", + " return batch" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "a2b895bd5e4e4a7381bc6fae39984049", + "9b4791d732dd46e3acc5f0357508b8f3", + "332380a3d4d246c6ba8277c77b5135ad", + "30a31ce44af046438a083cde3468a5cb", + "85f8c0305a9f49c0918d6c0bdefa7f7d", + "b45964d19f5345b681a3908d9f9169f5", + "f34f971e2b99408cb66c78af15dbc28f", + "af8367ceb4144911b7ed574a363b3650", + "2ea717347c644bf88715be129797e72f", + "bac18c216ef24b6b8f7c7eba3a216d97", + 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"version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + } + ], + "source": [ + "common_voice_train = common_voice_train.map(replace_english_letters)\n", + "common_voice_test = common_voice_test.map(replace_english_letters)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "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": 21, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "2b0dd8c0900541a19fc5be1ea22258a0", + "86a0171499974d918f3438b5f0e7f578", + "5cad57e30393460a9f5f4087a84e7396", + "6e989ad2dd964157822cbf693621b446", + "f8cea26f94cd441a8d603ac314500146", + "ef2e077488c7401da05f2e9ed06459a2", + 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\"/usr/local/lib/python3.7/dist-packages/huggingface_hub/commands/huggingface_cli.py\", line 41, in main\n", + " service.run()\n", + " File \"/usr/local/lib/python3.7/dist-packages/huggingface_hub/commands/user.py\", line 174, in run\n", + " _login(self._api, token=token)\n", + " File \"/usr/local/lib/python3.7/dist-packages/huggingface_hub/commands/user.py\", line 413, in _login\n", + " raise ValueError(\"Invalid token passed.\")\n", + "ValueError: Invalid token passed.\n" + ] + } + ], + "source": [ + "!huggingface-cli login" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 328, + "referenced_widgets": [ + "7ea7b10b956b42288bd9a3f8a1484daa", + "8e79d39d96af40968143ec5ef631413b", + "c56732f8e4164cc4a9f81155b5e71d80", + "e0ce872c6b4f4fcbb3e8fe6164388899", + "bb2100f2221c484dbbc1fcbba3536d20", + "36f55b249a604c118bda9a1ae1ee30e8", + "890c9f33360c45ab9a0e1fc943cd7fb7", + 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"376d41f0c5724fefa41619d66725df68", + "aaa121712e59473b9cac3ddfe76f0284", + "c8d9f71b73c34dedac6a06108cdffc85" + ] + }, + "id": "kFeWfVwYZKys", + "outputId": "971f71de-d7ba-4b34-d785-a76f8bd48c1c" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.7/dist-packages/huggingface_hub/hf_api.py:1004: FutureWarning: `create_repo` now takes `token` as an optional positional argument. Be sure to adapt your code!\n", + " FutureWarning,\n", + "Cloning https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1 into local empty directory.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7ea7b10b956b42288bd9a3f8a1484daa", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Download file pytorch_model.bin: 0%| | 3.47k/1.18G [00:00\n", + " \n", + " Your browser does not support the audio element.\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 37 + } + ], + "source": [ + "import IPython.display as ipd\n", + "import numpy as np\n", + "import random\n", + "\n", + "rand_int = random.randint(0, len(common_voice_train)-1)\n", + "\n", + "print(common_voice_train[rand_int][\"sentence\"])\n", + "ipd.Audio(data=common_voice_train[rand_int][\"audio\"][\"array\"], autoplay=True, rate=16000)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "EE5jG9PVZmWU", + "outputId": "62287142-3ce2-486f-cf2a-3f3cd6bc5d69" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Target text: तुम ने टॉम को कहाँ भेजा\n", + "Input array shape: (32832,)\n", + "Sampling rate: 16000\n" + ] + } + ], + "source": [ + "rand_int = random.randint(0, len(common_voice_train)-1)\n", + "\n", + "print(\"Target text:\", common_voice_train[rand_int][\"sentence\"])\n", + "print(\"Input array shape:\", common_voice_train[rand_int][\"audio\"][\"array\"].shape)\n", + "print(\"Sampling rate:\", common_voice_train[rand_int][\"audio\"][\"sampling_rate\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "id": "XobzwvyNZpxv" + }, + "outputs": [], + "source": [ + "def prepare_dataset(batch):\n", + " audio = batch[\"audio\"]\n", + "\n", + " # batched output is \"un-batched\"\n", + " batch[\"input_values\"] = processor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_values[0]\n", + " batch[\"input_length\"] = len(batch[\"input_values\"])\n", + " \n", + " with processor.as_target_processor():\n", + " batch[\"labels\"] = processor(batch[\"sentence\"]).input_ids\n", + " return batch" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "ad819734e880445882cc1c22be3957e2", + "dd43208c5720452b9632fd5b256437e1", + "5a969d1505f442e09cdc3bfe7f9ba731", + "47121ee2b91945b68787fabf4632c578", + "2ace8ebc95214f24b965a1b7e10a71ab", + "0d81fb79c72b4a6390aefd4f5b194717", + "c5f5cef742f04353a6a06a594b96629e", + "272e50eb921d402680f1c83a70059ceb", + "e1d004360115479b8cd3fa513c9cd3aa", + "b73eca3f52bc4722b3874e89121e5001", + "35cb6c112d9a4416b732ba9baa6d85c3", + "369ff370ad344a3b8e960e55cad70f90", + "1d628d519a1b4e80999d2cb501b951ea", + "6ce3badd57e14b97b35a1c7dee3b29c9", + "7360d5a6b7eb47fc8fc6331317845d3a", + "d62f14b9de5148fdbe5c0eba69830972", + "5e7345a16f2a40c5b3ae0349672145f5", + "e796e12efa9a4c6680dfaa8db200493f", + "e2420e47b9844b3caa56cfeab8cab62d", + "8f59fe83f56a47bf82fc83602950c3ce", + "fb59f37592404916b939ada43266cacb", + "1a9f544e69794ee7aa8cb891185a3523" + ] + }, + "id": "A7gT1EQMZsvz", + "outputId": "c89a5ac1-8410-492f-b83d-cefa901d7214" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ad819734e880445882cc1c22be3957e2", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "369ff370ad344a3b8e960e55cad70f90", + "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": 41, + "metadata": { + "id": "rAYCcrJFZubm" + }, + "outputs": [], + "source": [ + "import torch\n", + "\n", + "from dataclasses import dataclass, field\n", + "from typing import Any, Dict, List, Optional, Union\n", + "\n", + "@dataclass\n", + "class DataCollatorCTCWithPadding:\n", + " \"\"\"\n", + " Data collator that will dynamically pad the inputs received.\n", + " Args:\n", + " processor (:class:`~transformers.Wav2Vec2Processor`)\n", + " The processor used for proccessing the data.\n", + " padding (:obj:`bool`, :obj:`str` or :class:`~transformers.tokenization_utils_base.PaddingStrategy`, `optional`, defaults to :obj:`True`):\n", + " Select a strategy to pad the returned sequences (according to the model's padding side and padding index)\n", + " among:\n", + " * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single\n", + " sequence if provided).\n", + " * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the\n", + " maximum acceptable input length for the model if that argument is not provided.\n", + " * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of\n", + " different lengths).\n", + " \"\"\"\n", + "\n", + " processor: Wav2Vec2Processor\n", + " padding: Union[bool, str] = True\n", + "\n", + " def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:\n", + " # split inputs and labels since they have to be of different lenghts and need\n", + " # different padding methods\n", + " input_features = [{\"input_values\": feature[\"input_values\"]} for feature in features]\n", + " label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n", + "\n", + " batch = self.processor.pad(\n", + " input_features,\n", + " padding=self.padding,\n", + " return_tensors=\"pt\",\n", + " )\n", + " with self.processor.as_target_processor():\n", + " labels_batch = self.processor.pad(\n", + " label_features,\n", + " padding=self.padding,\n", + " return_tensors=\"pt\",\n", + " )\n", + "\n", + " # replace padding with -100 to ignore loss correctly\n", + " labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n", + "\n", + " batch[\"labels\"] = labels\n", + "\n", + " return batch" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "id": "k05sM3rsZzGS" + }, + "outputs": [], + "source": [ + "data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "id": "T1zgf2ZKZ1et", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "2a357b306c754f31b7fb251eb3cd2230", + "bbb4e6ced57c438d89b5bcce24f2b32a", + "8f184a6d3a1141b78b86ad8578f54c30", + "787376e350d14135843de4d06b8a48b2", + "721bd9a3d6744e44a24a2a4bdf6df6e1", + "0cb0467bd1df4389b006adf857638584", + "24e0217ce8d04774ae3685f3b37f782b", + "767b31c886824286be320b25672f4dbb", + "5484284a8f1542a7868ec56b80e21b5a", + "ab5577f97c004a139d71f7c19c175c1a", + "d4feadeb5aca4fba9f8cc3a65c20864b" + ] + }, + "outputId": "21e9d338-01a2-4ca3-f610-547b78be4027" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2a357b306c754f31b7fb251eb3cd2230", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/1.90k [00:00\n", + " \n", + " \n", + " [7350/7350 10:39:00, Epoch 49/50]\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", + " \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", + " \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", + "
StepTraining LossValidation LossWer
20012.2663005.9244651.000000
4004.1856003.4968181.000000
6003.3908002.9969571.000000
8001.5444000.9070840.613860
10000.7237000.6507730.486196
12000.5323000.6217120.464703
14000.4426000.5785240.428818
16000.3933000.5934670.421654
18000.3532000.6357760.446544
20000.3319000.5789380.411772
22000.2877000.6163390.405596
24000.2663000.6176410.389290
26000.2511000.6064830.399852
28000.2275000.6182920.384226
30000.2098000.6485600.386387
32000.1943000.6365250.388549
34000.1877000.6013320.367673
36000.1679000.6451410.379470
38000.1667000.6410350.363474
40000.1514000.6000080.357730
42000.1453000.6019750.351800
44000.1340000.6530950.351677
46000.1354000.6874020.357791
48000.1224000.6518930.349206
50000.1199000.6552860.349021
52000.1077000.6621120.342907
54000.0997000.6640620.341301
56000.0964000.6721870.338460
58000.0931000.6364850.336298
60000.0944000.6453990.332592
62000.0862000.6497300.325551
64000.0848000.6599330.322587
66000.0793000.6624820.323204
68000.0760000.6463040.318634
70000.0749000.6559350.322463
72000.0663000.6552390.319993

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200/preprocessor_config.json\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/preprocessor_config.json\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400/preprocessor_config.json\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-1800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-2800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-3800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-4800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-5800] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6000] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6200] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6400] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7000/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6600] due to args.save_total_limit\n", + "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", + "***** Running Evaluation *****\n", + " Num examples = 2095\n", + " Batch size = 8\n", + "Saving model checkpoint to wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/config.json\n", + "Model weights saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/pytorch_model.bin\n", + "Configuration saved in wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-7200/preprocessor_config.json\n", + "Deleting older checkpoint [wav2vec2-large-xls-r-300m-hi-wx1/checkpoint-6800] due to args.save_total_limit\n", + "\n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "TrainOutput(global_step=7350, training_loss=0.7602417024625402, metrics={'train_runtime': 38348.885, 'train_samples_per_second': 6.142, 'train_steps_per_second': 0.192, 'total_flos': 2.924018252332608e+19, 'train_loss': 0.7602417024625402, 'epoch': 50.0})" + ] + }, + "metadata": {}, + "execution_count": 49 + } + ], + "source": [ + "trainer.train()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 356, + "referenced_widgets": [ + "8d65fa93b17d40c1b4832a191abf8ba3", + "426e231855b84605ac24af1d7f800692", + "96b7c2c5062a4295aeaa24d1781e94b3", + "88ab94d74c774283b75d32496d1b1a5f", + "d01833fbb46443c7bc240e7d1cca61a9", + "6e55b8ac44b845c6abdc537d9eec6f90", + "0efd8286d24b46df9f0f8401fc4c87b4", + "5b2ec48d4d094a368eda80ebd4de72ee", + 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wav2vec2-large-xls-r-300m-hi-wx1/preprocessor_config.json\n", + "Several commits (2) will be pushed upstream.\n", + "The progress bars may be unreliable.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8d65fa93b17d40c1b4832a191abf8ba3", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "Upload file pytorch_model.bin: 0%| | 3.36k/1.18G [00:00 main\n", + "\n", + "Dropping the following result as it does not have all the necessary fields:\n", + "{'dataset': {'name': 'common_voice', 'type': 'common_voice', 'args': 'hi'}}\n", + "To https://huggingface.co/DrishtiSharma/wav2vec2-large-xls-r-300m-hi-wx1\n", + " 26465e2..a742827 main -> main\n", + "\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + 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