diff --git "a/greek_training_script.ipynb" "b/greek_training_script.ipynb" new file mode 100644--- /dev/null +++ "b/greek_training_script.ipynb" @@ -0,0 +1,8920 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "epSR1CyPu0-M" + }, + "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", + "source": [ + "%%capture\n", + "!pip install https://github.com/kpu/kenlm/archive/master.zip pyctcdecode\n", + "!pip install datasets==1.18.1\n", + "!pip install git+https://github.com/huggingface/transformers.git\n", + "!pip install huggingface_hub==0.1\n", + "!pip install torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html\n", + "!pip install jiwer" + ], + "metadata": { + "id": "FLe_Nq02u5jO" + }, + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": 2, + "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": { + "id": "GquuHi8Ju0-Q" + }, + "source": [ + "## Print main infos" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5P6I-W9ts-kR", + "outputId": "7a8adbe6-dc88-42ae-93b2-3e670f79030c" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic\n", + "CPU cores: 2\n", + "Python version: 3.7.12\n", + "PyTorch version: 1.10.0+cu111\n", + "GPU is visible: True\n", + "Transformers version: 4.17.0.dev0\n", + "Datasets version: 1.18.1\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": { + "id": "e9YhHNfbu0-S" + }, + "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": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "YT7fRnKctggU", + "outputId": "be0e697f-fd8f-4bbf-f929-4a1d48637b38" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Fri Jan 28 03:31:46 2022 \n", + "+-----------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 495.46 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 T4 Off | 00000000:00:04.0 Off | 0 |\n", + "| N/A 35C P8 9W / 70W | 3MiB / 15109MiB | 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": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241, + "referenced_widgets": [ + "506d22accd9a4738931752c6c743b8c5", + "35b07861c5f64921b37457ef8de2d46c", + "fa587ebcaaa54f558d1c13b1b0113fc8", + "7c28275ea90644a38706dbae1f4f8d2f", + "088411fa5833470383fcdc476c99bf6c", + "3bb166a55b2f492ba63aa674406fb167", + "9efdb892757f4825b5182a3551099bc1", + "630d58f2ba1f4c95b2252e98c0c3d680", + "a09dd8ff85d64404b5f93e2bdf9f79e3", + "1da443f51b794ff1b92ffe5f13275d8b", + "4aeff351b65145488713937e9fd15df1", + "6f085e4087b0436db43827be093ee6c8", + "ff17c34db37c440d8ce83c3ec6563d1d", + "27517fc2492047b09e9cef3b99afc47c", + "d35feca8b13e4f14bd56add4ba6690bc", + "d5e8ea08318b4604810d3ed78f260d72" + ] + }, + "id": "JXfFtOjZu0-T", + "outputId": "691803de-597f-4fa3-c25d-180288d41cbe" + }, + "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-crendential store but this isn't the helper defined on your machine.\n", + "You will have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal to set it 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", + "source": [ + "%%capture\n", + "!apt install git-lfs" + ], + "metadata": { + "id": "W4Yue2q1u-Np" + }, + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TorMtpwPv6RQ" + }, + "source": [ + "## Quick training run with a dummy model and data\n", + "more information on https://github.com/huggingface/transformers/tree/master/examples/pytorch/speech-recognition" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "fevoJD15u4Ss", + "outputId": "e9fc7c6f-4c84-4163-c23b-7ab6653747e9" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "--2022-01-28 03:34:16-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 30347 (30K) [text/plain]\n", + "Saving to: ‘run_speech_recognition_ctc.py’\n", + "\n", + "\r run_speec 0%[ ] 0 --.-KB/s \rrun_speech_recognit 100%[===================>] 29.64K --.-KB/s in 0.001s \n", + "\n", + "2022-01-28 03:34:16 (24.7 MB/s) - ‘run_speech_recognition_ctc.py’ saved [30347/30347]\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": 21, + "metadata": { + "id": "QPffzfr2u0-V" + }, + "outputs": [], + "source": [ + "# \t--learning_rate=\"7.5e-5\" \\\n", + "# 84.5" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Mz4bubhxxsad", + "outputId": "80a0e604-70d1-4348-c030-bb515fedd655", + "collapsed": true + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "01/28/2022 03:36:33 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True\n", + "01/28/2022 03:36:33 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "bf16=False,\n", + "bf16_full_eval=False,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_bucket_cap_mb=None,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=500,\n", + "evaluation_strategy=IntervalStrategy.STEPS,\n", + "fp16=True,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "gradient_checkpointing=True,\n", + "greater_is_better=None,\n", + "group_by_length=True,\n", + "half_precision_backend=auto,\n", + "hub_model_id=None,\n", + "hub_strategy=HubStrategy.EVERY_SAVE,\n", + "hub_token=,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=0.0003,\n", + "length_column_name=input_length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./wav2vec2-large-xls-r-300m-greek/runs/Jan28_03-36-32_1be27c3b03ee,\n", + "logging_first_step=False,\n", + "logging_nan_inf_filter=True,\n", + "logging_steps=100,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=100.0,\n", + "optim=OptimizerNames.ADAMW_HF,\n", + "output_dir=./wav2vec2-large-xls-r-300m-greek,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=32,\n", + "per_device_train_batch_size=32,\n", + "prediction_loss_only=False,\n", + "push_to_hub=True,\n", + "push_to_hub_model_id=None,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=,\n", + "remove_unused_columns=True,\n", + "report_to=['tensorboard'],\n", + "resume_from_checkpoint=None,\n", + "run_name=./wav2vec2-large-xls-r-300m-greek,\n", + "save_on_each_node=False,\n", + "save_steps=500,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=2,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tf32=None,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=500,\n", + "weight_decay=0.0,\n", + "xpu_backend=None,\n", + ")\n", + "01/28/2022 03:36:34 - WARNING - datasets.builder - Reusing dataset common_voice (/root/.cache/huggingface/datasets/mozilla-foundation___common_voice/el/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n", + "01/28/2022 03:36:36 - WARNING - datasets.builder - Reusing dataset common_voice (/root/.cache/huggingface/datasets/mozilla-foundation___common_voice/el/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n", + "01/28/2022 03:36:36 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/mozilla-foundation___common_voice/el/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b/cache-c88de5610ac14b24.arrow\n", + "01/28/2022 03:36:36 - WARNING - datasets.arrow_dataset - Loading cached processed dataset at /root/.cache/huggingface/datasets/mozilla-foundation___common_voice/el/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b/cache-29b6a8b15b8c03d6.arrow\n", + "loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/config.json from cache at /root/.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\": \"4.17.0.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, 6.58ba/s]\n", + "100% 1/1 [00:00<00:00, 19.09ba/s]\n", + "Didn't find file ./wav2vec2-large-xls-r-300m-greek/tokenizer.json. We won't load it.\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/vocab.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/tokenizer_config.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/added_tokens.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/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 /root/.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\": \"4.17.0.dev0\",\n", + " \"use_weighted_layer_sum\": false,\n", + " \"vocab_size\": 32,\n", + " \"xvector_output_dim\": 512\n", + "}\n", + "\n", + "https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/preprocessor_config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpfk9jtajv\n", + "Downloading: 100% 212/212 [00:00<00:00, 241kB/s]\n", + "storing https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/preprocessor_config.json in cache at /root/.cache/huggingface/transformers/6fb028b95b394059e7d3b367bbca2382b576c66aebe896f04d2cd34e1b575f5b.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326\n", + "creating metadata file for /root/.cache/huggingface/transformers/6fb028b95b394059e7d3b367bbca2382b576c66aebe896f04d2cd34e1b575f5b.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326\n", + "loading feature extractor configuration file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/preprocessor_config.json from cache at /root/.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", + "https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmp10cxxmf9\n", + "Downloading: 100% 1.18G/1.18G [00:58<00:00, 21.6MB/s]\n", + "storing https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/pytorch_model.bin in cache at /root/.cache/huggingface/transformers/1e6a6507f3b689035cd4b247e2a37c154e27f39143f31357a49b4e38baeccc36.1edb32803799e27ed554eb7dd935f6745b1a0b17b0ea256442fe24db6eb546cd\n", + "creating metadata file for /root/.cache/huggingface/transformers/1e6a6507f3b689035cd4b247e2a37c154e27f39143f31357a49b4e38baeccc36.1edb32803799e27ed554eb7dd935f6745b1a0b17b0ea256442fe24db6eb546cd\n", + "loading weights file https://huggingface.co/facebook/wav2vec2-xls-r-300m/resolve/main/pytorch_model.bin from cache at /root/.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.codevectors', 'project_hid.weight', 'project_hid.bias', 'quantizer.weight_proj.weight', 'project_q.weight', 'project_q.bias', 'quantizer.weight_proj.bias']\n", + "- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-300m and are newly initialized: ['lm_head.weight', 'lm_head.bias']\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: 3601ex [00:47, 76.50ex/s] \n", + "preprocess datasets: 1703ex [00:15, 110.56ex/s]\n", + "100% 4/4 [00:00<00:00, 362.84ba/s]\n", + "100% 2/2 [00:00<00:00, 645.67ba/s]\n", + "Downloading: 4.49kB [00:00, 3.53MB/s] \n", + "Configuration saved in ./wav2vec2-large-xls-r-300m-greek/preprocessor_config.json\n", + "tokenizer config file saved in ./wav2vec2-large-xls-r-300m-greek/tokenizer_config.json\n", + "Special tokens file saved in ./wav2vec2-large-xls-r-300m-greek/special_tokens_map.json\n", + "added tokens file saved in ./wav2vec2-large-xls-r-300m-greek/added_tokens.json\n", + "Configuration saved in ./wav2vec2-large-xls-r-300m-greek/config.json\n", + "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-greek/preprocessor_config.json\n", + "loading configuration file ./wav2vec2-large-xls-r-300m-greek/config.json\n", + "Model config Wav2Vec2Config {\n", + " \"_name_or_path\": \"./wav2vec2-large-xls-r-300m-greek\",\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\": 49,\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\": \"4.17.0.dev0\",\n", + " \"use_weighted_layer_sum\": false,\n", + " \"vocab_size\": 52,\n", + " \"xvector_output_dim\": 512\n", + "}\n", + "\n", + "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-greek/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-greek/tokenizer.json. We won't load it.\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/vocab.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/tokenizer_config.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/added_tokens.json\n", + "loading file ./wav2vec2-large-xls-r-300m-greek/special_tokens_map.json\n", + "loading file None\n", + "Adding to the vocabulary\n", + "Adding to the vocabulary\n", + "/usr/local/lib/python3.7/dist-packages/huggingface_hub/hf_api.py:718: FutureWarning: `create_repo` now takes `token` as an optional positional argument. Be sure to adapt your code!\n", + " FutureWarning,\n", + "/usr/local/lib/python3.7/dist-packages/huggingface_hub/hf_api.py:718: FutureWarning: `create_repo` now takes `token` as an optional positional argument. Be sure to adapt your code!\n", + " FutureWarning,\n", + "Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-greek into local empty directory.\n", + "01/28/2022 03:39:02 - WARNING - huggingface_hub.repository - Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-greek into local empty directory.\n", + "Download file pytorch_model.bin: 0% 3.47k/1.18G [00:00\n", + " main()\n", + " File \"run_speech_recognition_ctc.py\", line 688, in main\n", + " train_result = trainer.train(resume_from_checkpoint=checkpoint)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 1448, in train\n", + " self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 1573, in _maybe_log_save_evaluate\n", + " metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 2223, in evaluate\n", + " metric_key_prefix=metric_key_prefix,\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 2390, in evaluation_loop\n", + " loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 2598, in prediction_step\n", + " loss, outputs = self.compute_loss(model, inputs, return_outputs=True)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\", line 1980, in compute_loss\n", + " outputs = model(**inputs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\n", + " return forward_call(*input, **kwargs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py\", line 1747, in forward\n", + " return_dict=return_dict,\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\n", + " return forward_call(*input, **kwargs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py\", line 1332, in forward\n", + " extract_features = self.feature_extractor(input_values)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\n", + " return forward_call(*input, **kwargs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py\", line 500, in forward\n", + " hidden_states = conv_layer(hidden_states)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\n", + " return forward_call(*input, **kwargs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py\", line 375, in forward\n", + " hidden_states = self.layer_norm(hidden_states)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py\", line 1102, in _call_impl\n", + " return forward_call(*input, **kwargs)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/modules/normalization.py\", line 190, in forward\n", + " input, self.normalized_shape, self.weight, self.bias, self.eps)\n", + " File \"/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py\", line 2347, in layer_norm\n", + " return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backends.cudnn.enabled)\n", + "RuntimeError: CUDA out of memory. Tried to allocate 1.96 GiB (GPU 0; 14.76 GiB total capacity; 9.64 GiB already allocated; 785.75 MiB free; 12.51 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF\n", + " 4% 500/11300 [25:01<9:00:32, 3.00s/it]\n", + "\n", + " \u001b[A" + ] + } + ], + "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=\"el\" \\\n", + "\t--output_dir=\"./wav2vec2-large-xls-r-300m-greek\" \\\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" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true, + "id": "mT5MWR3Xu0-X", + "outputId": "9d2aafa9-8795-487b-8d47-531f5534d2df" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "01/28/2022 02:46:18 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True\n", + "01/28/2022 02:46:18 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n", + "_n_gpu=1,\n", + "adafactor=False,\n", + "adam_beta1=0.9,\n", + "adam_beta2=0.999,\n", + "adam_epsilon=1e-08,\n", + "bf16=False,\n", + "bf16_full_eval=False,\n", + "dataloader_drop_last=False,\n", + "dataloader_num_workers=0,\n", + "dataloader_pin_memory=True,\n", + "ddp_bucket_cap_mb=None,\n", + "ddp_find_unused_parameters=None,\n", + "debug=[],\n", + "deepspeed=None,\n", + "disable_tqdm=False,\n", + "do_eval=True,\n", + "do_predict=False,\n", + "do_train=True,\n", + "eval_accumulation_steps=None,\n", + "eval_steps=400,\n", + "evaluation_strategy=IntervalStrategy.STEPS,\n", + "fp16=True,\n", + "fp16_backend=auto,\n", + "fp16_full_eval=False,\n", + "fp16_opt_level=O1,\n", + "gradient_accumulation_steps=1,\n", + "gradient_checkpointing=True,\n", + "greater_is_better=None,\n", + "group_by_length=True,\n", + "half_precision_backend=auto,\n", + "hub_model_id=None,\n", + "hub_strategy=HubStrategy.EVERY_SAVE,\n", + "hub_token=,\n", + "ignore_data_skip=False,\n", + "label_names=None,\n", + "label_smoothing_factor=0.0,\n", + "learning_rate=7e-05,\n", + "length_column_name=input_length,\n", + "load_best_model_at_end=False,\n", + "local_rank=-1,\n", + "log_level=-1,\n", + "log_level_replica=-1,\n", + "log_on_each_node=True,\n", + "logging_dir=./wav2vec2-large-xls-r-300m-guarani/runs/Jan28_02-46-18_job-8be8b741-e32e-4579-bbec-1e00d9824b4f,\n", + "logging_first_step=False,\n", + "logging_nan_inf_filter=True,\n", + "logging_steps=100,\n", + "logging_strategy=IntervalStrategy.STEPS,\n", + "lr_scheduler_type=SchedulerType.LINEAR,\n", + "max_grad_norm=1.0,\n", + "max_steps=-1,\n", + "metric_for_best_model=None,\n", + "mp_parameters=,\n", + "no_cuda=False,\n", + "num_train_epochs=200.0,\n", + "optim=OptimizerNames.ADAMW_HF,\n", + "output_dir=./wav2vec2-large-xls-r-300m-guarani,\n", + "overwrite_output_dir=True,\n", + "past_index=-1,\n", + "per_device_eval_batch_size=32,\n", + "per_device_train_batch_size=32,\n", + "prediction_loss_only=False,\n", + "push_to_hub=True,\n", + "push_to_hub_model_id=None,\n", + "push_to_hub_organization=None,\n", + "push_to_hub_token=,\n", + "remove_unused_columns=True,\n", + "report_to=[],\n", + "resume_from_checkpoint=None,\n", + "run_name=./wav2vec2-large-xls-r-300m-guarani,\n", + "save_on_each_node=False,\n", + "save_steps=400,\n", + "save_strategy=IntervalStrategy.STEPS,\n", + "save_total_limit=2,\n", + "seed=42,\n", + "sharded_ddp=[],\n", + "skip_memory_metrics=True,\n", + "tf32=None,\n", + "tpu_metrics_debug=False,\n", + "tpu_num_cores=None,\n", + "use_legacy_prediction_loop=False,\n", + "warmup_ratio=0.0,\n", + "warmup_steps=400,\n", + "weight_decay=0.0,\n", + "xpu_backend=None,\n", + ")\n", + "Downloading and preparing dataset common_voice/gn to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/gn/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b...\n", + "Downloading: 100%|█████████████████████████| 33.2M/33.2M [00:04<00:00, 7.55MB/s]\n", + "Dataset common_voice downloaded and prepared to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/gn/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b. Subsequent calls will reuse this data.\n", + "01/28/2022 02:46:32 - WARNING - datasets.builder - Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/gn/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n", + "remove special characters from datasets: 100%|█| 298/298 [00:00<00:00, 7125.08ex\n", + "remove special characters from datasets: 100%|█| 134/134 [00:00<00:00, 7627.77ex\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, 91.49ba/s]\n", + "100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 238.62ba/s]\n", + "Didn't find file ./wav2vec2-large-xls-r-300m-guarani/tokenizer_config.json. We won't load it.\n", + "Didn't find file ./wav2vec2-large-xls-r-300m-guarani/added_tokens.json. We won't load it.\n", + "Didn't find file ./wav2vec2-large-xls-r-300m-guarani/special_tokens_map.json. We won't load it.\n", + "Didn't find file ./wav2vec2-large-xls-r-300m-guarani/tokenizer.json. We won't load it.\n", + "loading file ./wav2vec2-large-xls-r-300m-guarani/vocab.json\n", + "loading file None\n", + "loading file None\n", + "loading file None\n", + "loading file None\n", + "file ./wav2vec2-large-xls-r-300m-guarani/config.json not found\n", + "Adding to the vocabulary\n", + "Adding to the vocabulary\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\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.codevectors', 'project_q.bias', 'quantizer.weight_proj.weight', 'project_q.weight', 'quantizer.weight_proj.bias', 'project_hid.weight', 'project_hid.bias']\n", + "- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n", + "- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n", + "Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-300m and are newly initialized: ['lm_head.bias', 'lm_head.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "preprocess datasets: 100%|██████████���████████| 298/298 [00:01<00:00, 153.75ex/s]\n", + "preprocess datasets: 100%|███████████████████| 134/134 [00:00<00:00, 141.84ex/s]\n", + "100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 607.25ba/s]\n", + "100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 877.47ba/s]\n", + "Configuration saved in ./wav2vec2-large-xls-r-300m-guarani/preprocessor_config.json\n", + "tokenizer config file saved in ./wav2vec2-large-xls-r-300m-guarani/tokenizer_config.json\n", + "Special tokens file saved in ./wav2vec2-large-xls-r-300m-guarani/special_tokens_map.json\n", + "added tokens file saved in ./wav2vec2-large-xls-r-300m-guarani/added_tokens.json\n", + "Configuration saved in ./wav2vec2-large-xls-r-300m-guarani/config.json\n", + "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-guarani/preprocessor_config.json\n", + "loading configuration file ./wav2vec2-large-xls-r-300m-guarani/config.json\n", + "Model config Wav2Vec2Config {\n", + " \"_name_or_path\": \"./wav2vec2-large-xls-r-300m-guarani\",\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\": 41,\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\": 44,\n", + " \"xvector_output_dim\": 512\n", + "}\n", + "\n", + "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-guarani/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-guarani/tokenizer.json. We won't load it.\n", + "loading file ./wav2vec2-large-xls-r-300m-guarani/vocab.json\n", + "loading file ./wav2vec2-large-xls-r-300m-guarani/tokenizer_config.json\n", + "loading file ./wav2vec2-large-xls-r-300m-guarani/added_tokens.json\n", + "loading file ./wav2vec2-large-xls-r-300m-guarani/special_tokens_map.json\n", + "loading file None\n", + "Adding to the vocabulary\n", + "Adding to the vocabulary\n", + "Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-guarani into local empty directory.\n", + "01/28/2022 02:46:52 - WARNING - huggingface_hub.repository - Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-guarani into local empty directory.\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 = 298\n", + " Num Epochs = 200\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 = 2000\n", + "{'loss': 16.6077, 'learning_rate': 1.6975e-05, 'epoch': 10.0} \n", + "{'loss': 5.2501, 'learning_rate': 3.4475e-05, 'epoch': 20.0} \n", + "{'loss': 3.6008, 'learning_rate': 5.1974999999999996e-05, 'epoch': 30.0} \n", + "{'loss': 3.2047, 'learning_rate': 6.9475e-05, 'epoch': 40.0} \n", + " 20%|████████ | 400/2000 [10:28<35:31, 1.33s/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 = 134\n", + " Batch size = 32\n", + "\n", + " 0%| | 0/5 [00:00\n", + " \n", + " \n", + " \n", + " sentence\n", + " \n", + " \n", + " \n", + " \n", + " 0\n", + " του Δήμου Καρύστου Ευβοίας\n", + " \n", + " \n", + " 1\n", + " Ο Κακομοιρίδης, ακούοντας τις φωνές, βγήκε και αυτός\n", + " \n", + " \n", + " 2\n", + " και αργά, αλλά με βήμα κανονικό, ανέβηκε την ακροποταμιά\n", + " \n", + " \n", + " 3\n", + " Πήδηξε το Βασιλόπουλο πίσω του\n", + " \n", + " \n", + " 4\n", + " Μεγαλέμπορος στα ξένα, Αφέντη μου, αποκρίθηκε ο πρωτοβεστιάριος.\n", + " \n", + " \n", + " 5\n", + " που γύρευε να μας ζημιώσει.\n", + " \n", + " \n", + " 6\n", + " «Πολυτρανότατε Βασιλιά και ανεψιέ.\n", + " \n", + " \n", + " 7\n", + " Ποιος κλαίει;\n", + " \n", + " \n", + " 8\n", + " Ποιος είναι; ρώτησε από μέσα μια γυναικεία φωνή.\n", + " \n", + " \n", + " 9\n", + " Οι κύριοι που περίμεναν τη σειρά τους τον κοίταξαν αδιάφορα\n", + " \n", + " \n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {} + } + ], + "source": [ + "show_random_elements(common_voice_train.remove_columns([\"path\", \"audio\"]), num_examples=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "id": "p0mRPmRNu0-c" + }, + "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": 36, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "5501334e48a84b1eaf85753b0f36e230", + "720b283a227d4df1914f9bed388a09d5", + "2213ae0d586a4a339804dd8ad5a756cd", + "6a9b9b9f0f924a9ea298620c8f4e2fb6", + "1f8fc630966b4b3db90054f368261e5b", + "1022bb78bb994434886adadc86cd0c7c", + "90c51e69e0024bd0b3e37cd55186ef34", + "b6912421467f4ff3b2d9314c68ab5842", + "4af9c3299d6c441c97a77fa2222781b3", + "85b60caf17534a39a19184c7deea87c2", + "d4a54cfae3c048c28a212ff6ce939968", + "412700f967bb432d9d7d45236bfd412f", + "de104f53e608447db0db2e7af1b74182", + "c04e73e7b6c847bfa4dbe162205b7b8e", + "7bc37befa4a849719e7f07425fb9589d", + "a588fe64992648558253593fa5b3d0d9", + "440753103ee94491bc0ff99344ffab87", + "6a18a930146c46ff9989534822e17725", + "baf91a8779134a87a48c34c60e039c29", + "96ec10bc1e1e4cfcb3ea4e6038c628c0", + "dd067e6e637246708d1022067b3d2113", + "fce10bab4a2d4361b15eee46e9f6f8af" + ] + }, + "id": "agqzGAIMu0-c", + "outputId": "7b425866-f479-4a19-9e35-3a4d437f45b1" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5501334e48a84b1eaf85753b0f36e230", + "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": "412700f967bb432d9d7d45236bfd412f", + "version_minor": 0, + "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": 37, + "metadata": { + "id": "53AlYBMDu0-d" + }, + "outputs": [], + "source": [ + "# start_with_ar = common_voice_train.filter(lambda example: \"'\" in example['sentence'])\n", + "# start_with_ar[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "id": "rD0gtEmou0-d" + }, + "outputs": [], + "source": [ + "# start_with_ar" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "id": "xJRULzrSu0-d" + }, + "outputs": [], + "source": [ + "def replace_hatted_characters(batch):\n", + "# batch[\"sentence\"] = re.sub('[â]', 'a', batch[\"sentence\"])\n", + "# batch[\"sentence\"] = re.sub('[î]', 'i', batch[\"sentence\"])\n", + "# batch[\"sentence\"] = re.sub('[ô]', 'o', batch[\"sentence\"])\n", + "# batch[\"sentence\"] = re.sub('[û]', 'u', batch[\"sentence\"])\n", + " return batch" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "192a7f0c4eee4c419bcc5ccadd759e7c", + "3ccf0207ee774c11847443efe3e086d8", + "d38c1a4492034bc4bd63d6bc48372e35", + "d4a2e4b0b6204cfa80ca0cb5c950245e", + "07f91d6c45ec4d359cef8e1c1df556cc", + "24c89216eb204bc69d48cabd2284c1fd", + "92d0f05094a24170b920f0c7340dada2", + "ae49baef87d74c48980d6538128e953f", + "ba15bda03d254464999ba9b8444ea4f4", + "7f9a33dfc82041ee91cd02bdb431048f", + "5ecf664e916f4815af551f040a5214d1", + "b1b8456429134365bddc7d4455659707", + "46f54bdb935141a589e5f5a2de7b13b6", + "c0898ca05eb8445db76c62a55586a1d7", + "ec9baec03d2844169fb1ea07aa3ef4df", + "ec747a88d462468092adc85543104e3a", + "08440681ebf0422094cf3cc47c876deb", + "521c210abf8549f1b0b029c85128bd5b", + "456d873c4b0d43ce89240d273e1e61cb", + "8abf03d2ee6d4186a4c40c898e51816e", + "fa32fe18968d4d62b57f5e89eddcea74", + "26e0bb7815d44fc7b6a61de967526f2c" + ] + }, + "id": "hLAh7RO5u0-e", + "outputId": "ada190d8-067f-4dc7-bd4b-6620b98df276" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "192a7f0c4eee4c419bcc5ccadd759e7c", + "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": "b1b8456429134365bddc7d4455659707", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + "0ex [00:00, ?ex/s]" + ] + }, + "metadata": {} + } + ], + "source": [ + "common_voice_train = common_voice_train.map(replace_hatted_characters)\n", + "common_voice_test = common_voice_test.map(replace_hatted_characters)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "id": "nXVCeDwmu0-f" + }, + "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": 42, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 81, + "referenced_widgets": [ + "bfaf547bb5de47ecb0f61f49ee54ba81", + "8e4d4c249a1445fabbd4371ed4d87353", + "23a8cd7810c245ac9949628c39818df2", + "df77a14794c24a22b1676a83fa676e90", + "0b4b0815009f4b27b1ad87a902a72387", + "d12acd64b76f4da8a559e4f57946c7ff", + "6a36c1cbd1544ebf8887fff2e2db6d4f", + "18fdeeac144b470d8b1c7b503a45f830", + "40e6e444f6214db2929978e36912edbb", + "c47439d6d97e4c3abfaa18b4cc0922a9", + "f176dfc2a36e4df8ab6b6e889cb865c5", + "167a5c9f5adf4c8da1770dc385aee84b", + "03d81a2e990f4169880221312bed0f01", + "3c8265c24c0f44e7813e9c56116c30c5", + "121bd902f39e443d853bb49502f18b0c", + "09e39c613b3b4cefb65dea8717a9d15b", + "f5c7426f75554834b5fa9a28533ab4f9", + "902adb6401e34ee1810a83e608f1d155", + "5342c532e5ea47ceae57516244618554", + "ae3b191a8c75407a8ce5be8a907a8ee4", + "0d717e4fa2f940c4a2c11d7eaa86d0e8", + "3c9c69a1823349baa8b931cb9e71c982" + ] + }, + "id": "esAt_StOu0-f", + "outputId": "2c8aae9a-3d3b-4e4c-fd16-dd63e1d3923b" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bfaf547bb5de47ecb0f61f49ee54ba81", + "version_minor": 0, + "version_major": 2 + }, + "text/plain": [ + " 0%| | 0/1 [00:00] 4.63K --.-KB/s in 0s \n", + "\n", + "2022-01-27 16:52:27 (21.9 MB/s) - ‘eval.py’ saved [4738/4738]\n", + "\n", + "total 1232584\n", + "-rw-r--r-- 1 ovh ovh 399 Jan 27 12:09 vocab.json\n", + "-rw-r--r-- 1 ovh ovh 294 Jan 27 12:09 tokenizer_config.json\n", + "-rw-r--r-- 1 ovh ovh 695 Jan 27 12:09 special_tokens_map.json\n", + "-rw-r--r-- 1 ovh ovh 23 Jan 27 12:09 added_tokens.json\n", + "drwxr-xr-x 2 ovh ovh 4096 Jan 27 16:15 checkpoint-7500\n", + "drwxr-xr-x 2 ovh ovh 4096 Jan 27 16:31 checkpoint-8000\n", + "-rw-r--r-- 1 ovh ovh 197 Jan 27 16:43 train_results.json\n", + "-rw-r--r-- 1 ovh ovh 14654 Jan 27 16:43 trainer_state.json\n", + "-rw-r--r-- 1 ovh ovh 225 Jan 27 16:44 eval_results.json\n", + "-rw-r--r-- 1 ovh ovh 2033 Jan 27 16:44 config.json\n", + "-rw-r--r-- 1 ovh ovh 400 Jan 27 16:44 all_results.json\n", + "-rw-r--r-- 1 ovh ovh 1262083569 Jan 27 16:44 pytorch_model.bin\n", + "-rw-r--r-- 1 ovh ovh 3055 Jan 27 16:44 training_args.bin\n", + "-rw-r--r-- 1 ovh ovh 212 Jan 27 16:44 preprocessor_config.json\n", + "-rw-r--r-- 1 ovh ovh 2484 Jan 27 16:48 README.md\n", + "-rw-r--r-- 1 ovh ovh 4738 Jan 27 16:52 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-georgian\n", + "!ls -ltr wav2vec2-large-xls-r-300m-georgian" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Qa9QSlvhu0-h", + "outputId": "948d088f-0f7e-4c2f-d3c8-226f0040b71a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error: mkl-service + Intel(R) MKL: MKL_THREADING_LAYER=INTEL is incompatible with libgomp-a34b3233.so.1 library.\n", + "\tTry to import numpy first or set the threading layer accordingly. Set MKL_SERVICE_FORCE_INTEL to force it.\n" + ] + } + ], + "source": [ + "!cd wav2vec2-large-xls-r-300m-georgian; python eval.py \\\n", + " --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config ka --split test --log_outputs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lBxt3YqJu0-h" + }, + "outputs": [], + "source": [ + "!cd wav2vec2-large-xls-r-300m-georgian; python eval.py \\\n", + " --model_id infinitejoy/wav2vec2-large-xls-r-300m-georgian --dataset speech-recognition-community-v2/dev_data \\\n", + " --config ka --split validation --chunk_length_s 10 --stride_length_s 1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "referenced_widgets": [ + "24592b0be30e4eafb1949cf09d1c4fb4", + "f9bf2ab0d2fa4d3f9235cc6d1ab772f1", + "b0791474a34043da8057e06741472ade", + "1ccbd582d616458b87c76ac8dc5b6b36" + ] + }, + "id": "jnJFuiwou0-i", + "outputId": "92fcb6b6-59aa-465d-e38a-f38d2db6adfb" + }, + "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": null, + "metadata": { + "colab": { + "referenced_widgets": [ + "42ac3a57a96b4987b0c62aa41aa13702", + "29dbfe94c1e9436ea3feefd9a7ba5d34", + "acd0b1dccad24943bf760273d89aced3" + ] + }, + "id": "m6t_dfe4u0-i", + "outputId": "a81aeb22-0f83-4f95-cd2d-23972ce23da9" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/el/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "42ac3a57a96b4987b0c62aa41aa13702", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading: 0%| | 0.00/1.99k [00:00\nHugging Face\n
\nThe AI community building the future\n
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