{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# HuggingFace challenge - Debugger notebook\n", "Run this notebook to verify your libraries versions, check GPU config and run a quick training" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "id": "T2utsYSKszvv" }, "outputs": [], "source": [ "import platform\n", "import multiprocessing\n", "\n", "import torch\n", "import transformers\n", "import datasets\n", "\n", "import soundfile" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Print main infos" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5P6I-W9ts-kR", "outputId": "939bd550-1486-46a6-8371-e82ada0f448c" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Platform: Linux-5.11.0-37-generic-x86_64-with-glibc2.10\n", "CPU cores: 60\n", "Python version: 3.8.8\n", "PyTorch version: 1.10.1+cu102\n", "GPU is visible: True\n", "Transformers version: 4.16.0.dev0\n", "Datasets version: 1.17.1.dev0\n", "soundfile version: 0.10.3\n" ] } ], "source": [ "print(f\"Platform: {platform.platform()}\")\n", "print(f\"CPU cores: {multiprocessing.cpu_count()}\")\n", "\n", "print(f\"Python version: {platform.python_version()}\")\n", "\n", "print(f\"PyTorch version: {torch.__version__}\")\n", "print(f\"GPU is visible: {torch.cuda.is_available()}\")\n", "\n", "print(f\"Transformers version: {transformers.__version__}\")\n", "print(f\"Datasets version: {datasets.__version__}\")\n", "\n", "print(f\"soundfile version: {soundfile.__version__}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Check your GPU informations (if any)\n", "If you launched an AI Training job with GPU resources, they should be listed below (Tesla V100s 32GB).\n", "Driver and CUDA version " ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YT7fRnKctggU", "outputId": "f355a3e0-20da-489f-bd1f-5e508e792a68" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wed Jan 26 14:03:08 2022 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 |\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 V100S-PCI... Off | 00000000:00:06.0 Off | 0 |\n", "| N/A 40C P0 52W / 250W | 21343MiB / 32510MiB | 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", "+-----------------------------------------------------------------------------+\n" ] } ], "source": [ "!nvidia-smi" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2fa897b4afc049229144599af9e3f807", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(HTML(value='
\\n] 29.64K --.-KB/s in 0.001s \n", "\n", "2022-01-22 15:01:09 (20.1 MB/s) - ‘run_speech_recognition_ctc.py’ saved [30348/30348]\n", "\n" ] } ], "source": [ "!wget -O run_speech_recognition_ctc.py https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# \t--learning_rate=\"7.5e-5\" \\\n", "# 84.5" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Mz4bubhxxsad", "outputId": "23398525-cc19-43c2-9fec-497e06214f29" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "remove special characters from datasets: 100%|█| 1794/1794 [00:00<00:00, 4500.40\n", "remove special characters from datasets: 100%|█| 810/810 [00:00<00:00, 7132.38ex\n", "loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/config.json from cache at /workspace/.cache/huggingface/transformers/dabc27df63e37bd2a7a221c7774e35f36a280fbdf917cf54cadfc7df8c786f6f.a3e4c3c967d9985881e0ae550a5f6f668f897db5ab2e0802f9b97973b15970e6\n", "Model config Wav2Vec2Config {\n", " \"_name_or_path\": \"facebook/wav2vec2-xls-r-300m\",\n", " \"activation_dropout\": 0.0,\n", " \"adapter_kernel_size\": 3,\n", " \"adapter_stride\": 2,\n", " \"add_adapter\": false,\n", " \"apply_spec_augment\": true,\n", " \"architectures\": [\n", " \"Wav2Vec2ForPreTraining\"\n", " ],\n", " \"attention_dropout\": 0.1,\n", " \"bos_token_id\": 1,\n", " \"classifier_proj_size\": 256,\n", " \"codevector_dim\": 768,\n", " \"contrastive_logits_temperature\": 0.1,\n", " \"conv_bias\": true,\n", " \"conv_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512\n", " ],\n", " \"conv_kernel\": [\n", " 10,\n", " 3,\n", " 3,\n", " 3,\n", " 3,\n", " 2,\n", " 2\n", " ],\n", " \"conv_stride\": [\n", " 5,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2\n", " ],\n", " \"ctc_loss_reduction\": \"sum\",\n", " \"ctc_zero_infinity\": false,\n", " \"diversity_loss_weight\": 0.1,\n", " \"do_stable_layer_norm\": true,\n", " \"eos_token_id\": 2,\n", " \"feat_extract_activation\": \"gelu\",\n", " \"feat_extract_dropout\": 0.0,\n", " \"feat_extract_norm\": \"layer\",\n", " \"feat_proj_dropout\": 0.1,\n", " \"feat_quantizer_dropout\": 0.0,\n", " \"final_dropout\": 0.0,\n", " \"gradient_checkpointing\": false,\n", " \"hidden_act\": \"gelu\",\n", " \"hidden_dropout\": 0.1,\n", " \"hidden_size\": 1024,\n", " \"initializer_range\": 0.02,\n", " \"intermediate_size\": 4096,\n", " \"layer_norm_eps\": 1e-05,\n", " \"layerdrop\": 0.1,\n", " \"mask_feature_length\": 10,\n", " \"mask_feature_min_masks\": 0,\n", " \"mask_feature_prob\": 0.0,\n", " \"mask_time_length\": 10,\n", " \"mask_time_min_masks\": 2,\n", " \"mask_time_prob\": 0.075,\n", " \"model_type\": \"wav2vec2\",\n", " \"num_adapter_layers\": 3,\n", " \"num_attention_heads\": 16,\n", " \"num_codevector_groups\": 2,\n", " \"num_codevectors_per_group\": 320,\n", " \"num_conv_pos_embedding_groups\": 16,\n", " \"num_conv_pos_embeddings\": 128,\n", " \"num_feat_extract_layers\": 7,\n", " \"num_hidden_layers\": 24,\n", " \"num_negatives\": 100,\n", " \"output_hidden_size\": 1024,\n", " \"pad_token_id\": 0,\n", " \"proj_codevector_dim\": 768,\n", " \"tdnn_dilation\": [\n", " 1,\n", " 2,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"tdnn_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 1500\n", " ],\n", " \"tdnn_kernel\": [\n", " 5,\n", " 3,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.16.0.dev0\",\n", " \"use_weighted_layer_sum\": false,\n", " \"vocab_size\": 32,\n", " \"xvector_output_dim\": 512\n", "}\n", "\n", "100%|█████████████████████████████████████████████| 1/1 [00:00<00:00, 11.99ba/s]\n", "100%|█████████████████████████████████████████████| 1/1 [00:00<00:00, 35.85ba/s]\n", "Didn't find file ./wav2vec2-large-xls-r-300m-chuvash/tokenizer.json. We won't load it.\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/vocab.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/tokenizer_config.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/added_tokens.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/special_tokens_map.json\n", "loading file None\n", "Adding to the vocabulary\n", "Adding to the vocabulary\n", "loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/config.json from cache at /workspace/.cache/huggingface/transformers/dabc27df63e37bd2a7a221c7774e35f36a280fbdf917cf54cadfc7df8c786f6f.a3e4c3c967d9985881e0ae550a5f6f668f897db5ab2e0802f9b97973b15970e6\n", "Model config Wav2Vec2Config {\n", " \"_name_or_path\": \"facebook/wav2vec2-xls-r-300m\",\n", " \"activation_dropout\": 0.0,\n", " \"adapter_kernel_size\": 3,\n", " \"adapter_stride\": 2,\n", " \"add_adapter\": false,\n", " \"apply_spec_augment\": true,\n", " \"architectures\": [\n", " \"Wav2Vec2ForPreTraining\"\n", " ],\n", " \"attention_dropout\": 0.1,\n", " \"bos_token_id\": 1,\n", " \"classifier_proj_size\": 256,\n", " \"codevector_dim\": 768,\n", " \"contrastive_logits_temperature\": 0.1,\n", " \"conv_bias\": true,\n", " \"conv_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512\n", " ],\n", " \"conv_kernel\": [\n", " 10,\n", " 3,\n", " 3,\n", " 3,\n", " 3,\n", " 2,\n", " 2\n", " ],\n", " \"conv_stride\": [\n", " 5,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2\n", " ],\n", " \"ctc_loss_reduction\": \"sum\",\n", " \"ctc_zero_infinity\": false,\n", " \"diversity_loss_weight\": 0.1,\n", " \"do_stable_layer_norm\": true,\n", " \"eos_token_id\": 2,\n", " \"feat_extract_activation\": \"gelu\",\n", " \"feat_extract_dropout\": 0.0,\n", " \"feat_extract_norm\": \"layer\",\n", " \"feat_proj_dropout\": 0.1,\n", " \"feat_quantizer_dropout\": 0.0,\n", " \"final_dropout\": 0.0,\n", " \"gradient_checkpointing\": false,\n", " \"hidden_act\": \"gelu\",\n", " \"hidden_dropout\": 0.1,\n", " \"hidden_size\": 1024,\n", " \"initializer_range\": 0.02,\n", " \"intermediate_size\": 4096,\n", " \"layer_norm_eps\": 1e-05,\n", " \"layerdrop\": 0.1,\n", " \"mask_feature_length\": 10,\n", " \"mask_feature_min_masks\": 0,\n", " \"mask_feature_prob\": 0.0,\n", " \"mask_time_length\": 10,\n", " \"mask_time_min_masks\": 2,\n", " \"mask_time_prob\": 0.075,\n", " \"model_type\": \"wav2vec2\",\n", " \"num_adapter_layers\": 3,\n", " \"num_attention_heads\": 16,\n", " \"num_codevector_groups\": 2,\n", " \"num_codevectors_per_group\": 320,\n", " \"num_conv_pos_embedding_groups\": 16,\n", " \"num_conv_pos_embeddings\": 128,\n", " \"num_feat_extract_layers\": 7,\n", " \"num_hidden_layers\": 24,\n", " \"num_negatives\": 100,\n", " \"output_hidden_size\": 1024,\n", " \"pad_token_id\": 0,\n", " \"proj_codevector_dim\": 768,\n", " \"tdnn_dilation\": [\n", " 1,\n", " 2,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"tdnn_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 1500\n", " ],\n", " \"tdnn_kernel\": [\n", " 5,\n", " 3,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.16.0.dev0\",\n", " \"use_weighted_layer_sum\": false,\n", " \"vocab_size\": 32,\n", " \"xvector_output_dim\": 512\n", "}\n", "\n", "loading feature extractor configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/preprocessor_config.json from cache at /workspace/.cache/huggingface/transformers/6fb028b95b394059e7d3b367bbca2382b576c66aebe896f04d2cd34e1b575f5b.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326\n", "Feature extractor Wav2Vec2FeatureExtractor {\n", " \"do_normalize\": true,\n", " \"feature_extractor_type\": \"Wav2Vec2FeatureExtractor\",\n", " \"feature_size\": 1,\n", " \"padding_side\": \"right\",\n", " \"padding_value\": 0,\n", " \"return_attention_mask\": true,\n", " \"sampling_rate\": 16000\n", "}\n", "\n", "loading weights file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/pytorch_model.bin from cache at /workspace/.cache/huggingface/transformers/1e6a6507f3b689035cd4b247e2a37c154e27f39143f31357a49b4e38baeccc36.1edb32803799e27ed554eb7dd935f6745b1a0b17b0ea256442fe24db6eb546cd\n", "Some weights of the model checkpoint at facebook/wav2vec2-xls-r-300m were not used when initializing Wav2Vec2ForCTC: ['quantizer.weight_proj.weight', 'quantizer.codevectors', 'project_q.bias', 'quantizer.weight_proj.bias', 'project_hid.bias', 'project_q.weight', 'project_hid.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", "preprocess datasets: 100%|█████████████████| 1794/1794 [00:15<00:00, 114.24ex/s]\n", "preprocess datasets: 100%|███████████████████| 810/810 [00:07<00:00, 108.63ex/s]\n", "100%|████████████████████████████████████████████| 2/2 [00:00<00:00, 713.44ba/s]\n", "100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 742.75ba/s]\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-chuvash/preprocessor_config.json\n", "tokenizer config file saved in ./wav2vec2-large-xls-r-300m-chuvash/tokenizer_config.json\n", "Special tokens file saved in ./wav2vec2-large-xls-r-300m-chuvash/special_tokens_map.json\n", "added tokens file saved in ./wav2vec2-large-xls-r-300m-chuvash/added_tokens.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-chuvash/config.json\n", "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-chuvash/preprocessor_config.json\n", "loading configuration file ./wav2vec2-large-xls-r-300m-chuvash/config.json\n", "Model config Wav2Vec2Config {\n", " \"_name_or_path\": \"./wav2vec2-large-xls-r-300m-chuvash\",\n", " \"activation_dropout\": 0.1,\n", " \"adapter_kernel_size\": 3,\n", " \"adapter_stride\": 2,\n", " \"add_adapter\": false,\n", " \"apply_spec_augment\": true,\n", " \"architectures\": [\n", " \"Wav2Vec2ForPreTraining\"\n", " ],\n", " \"attention_dropout\": 0.0,\n", " \"bos_token_id\": 1,\n", " \"classifier_proj_size\": 256,\n", " \"codevector_dim\": 768,\n", " \"contrastive_logits_temperature\": 0.1,\n", " \"conv_bias\": true,\n", " \"conv_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 512\n", " ],\n", " \"conv_kernel\": [\n", " 10,\n", " 3,\n", " 3,\n", " 3,\n", " 3,\n", " 2,\n", " 2\n", " ],\n", " \"conv_stride\": [\n", " 5,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2,\n", " 2\n", " ],\n", " \"ctc_loss_reduction\": \"mean\",\n", " \"ctc_zero_infinity\": false,\n", " \"diversity_loss_weight\": 0.1,\n", " \"do_stable_layer_norm\": true,\n", " \"eos_token_id\": 2,\n", " \"feat_extract_activation\": \"gelu\",\n", " \"feat_extract_dropout\": 0.0,\n", " \"feat_extract_norm\": \"layer\",\n", " \"feat_proj_dropout\": 0.0,\n", " \"feat_quantizer_dropout\": 0.0,\n", " \"final_dropout\": 0.0,\n", " \"hidden_act\": \"gelu\",\n", " \"hidden_dropout\": 0.0,\n", " \"hidden_size\": 1024,\n", " \"initializer_range\": 0.02,\n", " \"intermediate_size\": 4096,\n", " \"layer_norm_eps\": 1e-05,\n", " \"layerdrop\": 0.0,\n", " \"mask_feature_length\": 64,\n", " \"mask_feature_min_masks\": 0,\n", " \"mask_feature_prob\": 0.25,\n", " \"mask_time_length\": 10,\n", " \"mask_time_min_masks\": 2,\n", " \"mask_time_prob\": 0.75,\n", " \"model_type\": \"wav2vec2\",\n", " \"num_adapter_layers\": 3,\n", " \"num_attention_heads\": 16,\n", " \"num_codevector_groups\": 2,\n", " \"num_codevectors_per_group\": 320,\n", " \"num_conv_pos_embedding_groups\": 16,\n", " \"num_conv_pos_embeddings\": 128,\n", " \"num_feat_extract_layers\": 7,\n", " \"num_hidden_layers\": 24,\n", " \"num_negatives\": 100,\n", " \"output_hidden_size\": 1024,\n", " \"pad_token_id\": 43,\n", " \"proj_codevector_dim\": 768,\n", " \"tdnn_dilation\": [\n", " 1,\n", " 2,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"tdnn_dim\": [\n", " 512,\n", " 512,\n", " 512,\n", " 512,\n", " 1500\n", " ],\n", " \"tdnn_kernel\": [\n", " 5,\n", " 3,\n", " 3,\n", " 1,\n", " 1\n", " ],\n", " \"torch_dtype\": \"float32\",\n", " \"transformers_version\": \"4.16.0.dev0\",\n", " \"use_weighted_layer_sum\": false,\n", " \"vocab_size\": 46,\n", " \"xvector_output_dim\": 512\n", "}\n", "\n", "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-chuvash/preprocessor_config.json\n", "Feature extractor Wav2Vec2FeatureExtractor {\n", " \"do_normalize\": true,\n", " \"feature_extractor_type\": \"Wav2Vec2FeatureExtractor\",\n", " \"feature_size\": 1,\n", " \"padding_side\": \"right\",\n", " \"padding_value\": 0,\n", " \"return_attention_mask\": true,\n", " \"sampling_rate\": 16000\n", "}\n", "\n", "Didn't find file ./wav2vec2-large-xls-r-300m-chuvash/tokenizer.json. We won't load it.\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/vocab.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/tokenizer_config.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/added_tokens.json\n", "loading file ./wav2vec2-large-xls-r-300m-chuvash/special_tokens_map.json\n", "loading file None\n", "Adding to the vocabulary\n", "Adding to the vocabulary\n", "/workspace/votic_training/./wav2vec2-large-xls-r-300m-chuvash is already a clone of https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-chuvash. Make sure you pull the latest changes with `repo.git_pull()`.\n", "Using amp half precision backend\n", "The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "/opt/conda/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 = 1794\n", " Num Epochs = 100\n", " Instantaneous batch size per device = 32\n", " Total train batch size (w. parallel, distributed & accumulation) = 32\n", " Gradient Accumulation steps = 1\n", " Total optimization steps = 5700\n", " 9%|███▎ | 500/5700 [12:20<2:24:45, 1.67s/it]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 = 810\n", " Batch size = 32\n", "\n", " 0%| | 0/26 [00:00 main\n", "\n", "Upload file pytorch_model.bin: 100%|███████| 1.18G/1.18G [00:42<00:00, 29.8MB/s]\n", "Dropping the following result as it does not have all the necessary fields:\n", "{'dataset': {'name': 'MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CV', 'type': 'common_voice', 'args': 'Config: cv, Training split: train+validation, Eval split: test'}}\n", "To https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-chuvash\n", " 34ac9cc..1be96ec main -> main\n", "\n" ] } ], "source": [ "!python run_speech_recognition_ctc.py \\\n", "\t--dataset_name=\"mozilla-foundation/common_voice_7_0\" \\\n", "\t--model_name_or_path=\"facebook/wav2vec2-xls-r-300m\" \\\n", "\t--dataset_config_name=\"cv\" \\\n", "\t--output_dir=\"./wav2vec2-large-xls-r-300m-chuvash\" \\\n", "\t--overwrite_output_dir \\\n", "\t--num_train_epochs=\"100\" \\\n", "\t--per_device_train_batch_size=\"32\" \\\n", "\t--per_device_eval_batch_size=\"32\" \\\n", "\t--gradient_accumulation_steps=\"1\" \\\n", "\t--learning_rate=\"3e-4\" \\\n", "\t--warmup_steps=\"500\" \\\n", "\t--length_column_name=\"input_length\" \\\n", "\t--evaluation_strategy=\"steps\" \\\n", "\t--text_column_name=\"sentence\" \\\n", "\t--chars_to_ignore , ? . ! \\- \\; \\: \\\" “ % ‘ ” � — ’ … – \\\n", "\t--save_steps=\"500\" \\\n", "\t--eval_steps=\"500\" \\\n", "\t--logging_steps=\"100\" \\\n", "\t--layerdrop=\"0.0\" \\\n", "\t--activation_dropout=\"0.1\" \\\n", "\t--save_total_limit=\"2\" \\\n", "\t--freeze_feature_encoder \\\n", "\t--feat_proj_dropout=\"0.0\" \\\n", "\t--mask_time_prob=\"0.75\" \\\n", "\t--mask_time_length=\"10\" \\\n", "\t--mask_feature_prob=\"0.25\" \\\n", "\t--mask_feature_length=\"64\" \\\n", "\t--gradient_checkpointing \\\n", "\t--use_auth_token \\\n", "\t--fp16 \\\n", "\t--group_by_length \\\n", "\t--do_train --do_eval \\\n", " --push_to_hub > out.log" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "# !rm -rf wav2vec2-large-xls-r-300m-bashkir" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!ls -ltr" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Filesystem Size Used Avail Use% Mounted on\n", "overlay 3.5T 963G 2.4T 29% /\n", "tmpfs 64M 0 64M 0% /dev\n", "tmpfs 87G 0 87G 0% /sys/fs/cgroup\n", "tmpfs 87G 8.0K 87G 1% /dev/shm\n", "/dev/md0 3.5T 963G 2.4T 29% /etc/group\n", "tmpfs 87G 12K 87G 1% /proc/driver/nvidia\n", "/dev/vda1 49G 6.4G 42G 14% /usr/bin/nvidia-smi\n", "udev 87G 0 87G 0% /dev/nvidia0\n", "tmpfs 87G 0 87G 0% /proc/acpi\n", "tmpfs 87G 0 87G 0% /proc/scsi\n", "tmpfs 87G 0 87G 0% /sys/firmware\n" ] } ], "source": [ "!df -h" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading and preparing dataset common_voice/cv to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cv/7.0.0/33e08856cfa0d0665e837bcad73ffd920a0bc713ce8c5fffb55dbdf1c084d5ba...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d664c297fdc04696b86c7faddfa293f1", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/486M [00:00\n", " \n", " \n", " \n", " sentence\n", " \n", " \n", " \n", " \n", " 0\n", " Вӗри чейпе пӗрле икӗ булка параҫҫӗ.\n", " \n", " \n", " 1\n", " Ҫак тӗнчене ырӑрах, ҫутӑрах тӑвакансем кирлех.\n", " \n", " \n", " 2\n", " Тавара туяннине ӗнентерекен документсене упрамалла.\n", " \n", " \n", " 3\n", " Кӑҫал фильмсене Ҫӗмӗрле, Улатӑр хулисенчи кинотеатрӗсенче те кӑтартӗҫ.\n", " \n", " \n", " 4\n", " Чӑваш Енре чӑваш чӗлхи предмечӗ пирки хӗрсе калаҫаҫҫӗ.\n", " \n", " \n", " 5\n", " Ун чухне ҫапла апатланайнӑ-ши?\n", " \n", " \n", " 6\n", " Вӗсене тепӗр хут туясчӗ.\n", " \n", " \n", " 7\n", " Занятисене пырӑр.\n", " \n", " \n", " 8\n", " Шала кайнӑ чиртен сывалма кӑткӑс.\n", " \n", " \n", " 9\n", " Вӗсене «Хӑрушсӑр тата пахалӑхлӑ ҫулсем» федераци программипе килӗшӳллӗн юсӗҫ.\n", " \n", " \n", "" ], "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": 28, "metadata": {}, "outputs": [], "source": [ "import re\n", "chars_to_remove_regex = '[\\,\\?\\.\\!\\-\\;\\:\\\"\\“\\%\\‘\\”\\�\\—\\’\\…\\–]'\n", "\n", "def remove_special_characters(batch):\n", " batch[\"sentence\"] = re.sub(chars_to_remove_regex, '', batch[\"sentence\"]).lower()\n", " return batch" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "38286f69f9bd4d0a9979d0e247d13463", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1794 [00:00 main\n", "\n" ] }, { "data": { "text/plain": [ "'https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-chuvash/commit/f0fd0b1a9a8b5065f7c708f6633b736246777617'" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vocab_dict[\"|\"] = vocab_dict[\" \"]\n", "del vocab_dict[\" \"]\n", "\n", "vocab_dict[\"[UNK]\"] = len(vocab_dict)\n", "vocab_dict[\"[PAD]\"] = len(vocab_dict)\n", "print(len(vocab_dict))\n", "\n", "import json\n", "with open('./vocab.json', 'w') as vocab_file:\n", " json.dump(vocab_dict, vocab_file)\n", " \n", "from transformers import Wav2Vec2CTCTokenizer\n", "\n", "tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(\"./\", unk_token=\"[UNK]\", pad_token=\"[PAD]\", word_delimiter_token=\"|\")\n", "\n", "repo_name = \"wav2vec2-large-xls-r-300m-chuvash\"\n", "\n", "tokenizer.push_to_hub(repo_name)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2022-01-25 05:51:53-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/research_projects/robust-speech-event/eval.py\n", "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.110.133, 185.199.111.133, ...\n", "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 4421 (4.3K) [text/plain]\n", "Saving to: ‘eval.py’\n", "\n", "eval.py 100%[===================>] 4.32K --.-KB/s in 0s \n", "\n", "2022-01-25 05:51:53 (11.6 MB/s) - ‘eval.py’ saved [4421/4421]\n", "\n", "total 1232556\n", "-rw-r--r-- 1 ovh ovh 272 Jan 25 02:49 vocab.json\n", "-rw-r--r-- 1 ovh ovh 260 Jan 25 02:49 tokenizer_config.json\n", "-rw-r--r-- 1 ovh ovh 309 Jan 25 02:49 special_tokens_map.json\n", "-rw-r--r-- 1 ovh ovh 23 Jan 25 02:49 added_tokens.json\n", "drwxr-xr-x 2 ovh ovh 4096 Jan 25 05:21 checkpoint-5500\n", "drwxr-xr-x 2 ovh ovh 4096 Jan 25 05:35 checkpoint-6000\n", "-rw-r--r-- 1 ovh ovh 197 Jan 25 05:46 train_results.json\n", "-rw-r--r-- 1 ovh ovh 11278 Jan 25 05:46 trainer_state.json\n", "-rw-r--r-- 1 ovh ovh 224 Jan 25 05:46 eval_results.json\n", "-rw-r--r-- 1 ovh ovh 2033 Jan 25 05:46 config.json\n", "-rw-r--r-- 1 ovh ovh 399 Jan 25 05:46 all_results.json\n", "-rw-r--r-- 1 ovh ovh 1262058993 Jan 25 05:46 pytorch_model.bin\n", "-rw-r--r-- 1 ovh ovh 3055 Jan 25 05:46 training_args.bin\n", "-rw-r--r-- 1 ovh ovh 212 Jan 25 05:46 preprocessor_config.json\n", "-rw-r--r-- 1 ovh ovh 2253 Jan 25 05:49 README.md\n", "-rw-r--r-- 1 ovh ovh 4421 Jan 25 05:51 eval.py\n" ] } ], "source": [ "!wget -O eval.py https://raw.githubusercontent.com/huggingface/transformers/master/examples/research_projects/robust-speech-event/eval.py\n", "!cp eval.py wav2vec2-large-xls-r-300m-chuvash\n", "!ls -ltr wav2vec2-large-xls-r-300m-chuvash" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/bas/7.0.0/33e08856cfa0d0665e837bcad73ffd920a0bc713ce8c5fffb55dbdf1c084d5ba)\n", "100%|█████████████████████████████████████████| 375/375 [03:03<00:00, 2.04ex/s]\n", "WER: 1.0408274360370169\n", "CER: 2.2848350566223536\n", "100%|██████████████████████████████████████| 375/375 [00:00<00:00, 20474.93ex/s]\n" ] } ], "source": [ "!cd wav2vec2-large-xls-r-300m-chuvash; python eval.py --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config cv --split test --log_outputs" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "24592b0be30e4eafb1949cf09d1c4fb4", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/260 [00:00\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mlogits\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_values\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlogits\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mlogits\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogits\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mAssertionError\u001b[0m: 55" ] } ], "source": [ "# from transformers import AutoModelForCTC, AutoProcessor\n", "# from datasets import load_dataset\n", "\n", "# model = AutoModelForCTC.from_pretrained(\"infinitejoy/wav2vec2-large-xls-r-300m-bashkir\")\n", "# processor = AutoProcessor.from_pretrained(\"infinitejoy/wav2vec2-large-xls-r-300m-bashkir\")\n", "\n", "# input_values = processor(common_voice_test[0][\"audio\"][\"array\"], return_tensors=\"pt\", sampling_rate=16_000).input_values\n", "# # input_values = input_values.to(\"cuda\")\n", "\n", "# logits = model(input_values).logits\n", "\n", "# assert logits.shape[-1] == 32, logits.shape[-1]" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cv/7.0.0/33e08856cfa0d0665e837bcad73ffd920a0bc713ce8c5fffb55dbdf1c084d5ba)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "77ddec247efe46658e96cce814c59016", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/1.99k [00:00