{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "ZG_P29nKcSeI" }, "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": 1, "metadata": { "id": "YacvHugMc1Ka" }, "outputs": [], "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\n", "# !pip install -U git+https://github.com/huggingface/transformers.git" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "vy63SoiZbnB5", "outputId": "17391c60-b894-4571-b8a4-d46b18cb42e2" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting git+https://github.com/huggingface/transformers.git\n", " Cloning https://github.com/huggingface/transformers.git to /tmp/pip-req-build-i45amciw\n", " Running command git clone -q https://github.com/huggingface/transformers.git /tmp/pip-req-build-i45amciw\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: huggingface-hub<1.0,>=0.1.0 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (0.1.0)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (3.4.2)\n", "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (4.10.1)\n", "Requirement already satisfied: tokenizers!=0.11.3,>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (0.11.4)\n", "Requirement already satisfied: sacremoses in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (0.0.47)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (1.19.5)\n", "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (4.62.3)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (2.23.0)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (6.0)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (21.3)\n", "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.17.0.dev0) (2019.12.20)\n", "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from huggingface-hub<1.0,>=0.1.0->transformers==4.17.0.dev0) (3.10.0.2)\n", "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->transformers==4.17.0.dev0) (3.0.7)\n", "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->transformers==4.17.0.dev0) (3.7.0)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (2.10)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (2021.10.8)\n", "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (3.0.4)\n", "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==4.17.0.dev0) (1.24.3)\n", "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (1.15.0)\n", "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (1.1.0)\n", "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.17.0.dev0) (7.1.2)\n" ] } ], "source": [ "# !pip install -U git+https://github.com/huggingface/transformers.git" ] }, { "cell_type": "code", "execution_count": 1, "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": "ejKNEyJEcSeO" }, "source": [ "## Print main infos" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5P6I-W9ts-kR", "outputId": "bd0c00d8-91c9-4b1a-8f2c-24182c2b227f" }, "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": { "id": "_VUKw21PcSeQ" }, "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": "1fb2c851-11c3-4fcd-ad23-9032f25d7f8d" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sat Jan 29 03:27:00 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 35C P0 26W / 250W | 4MiB / 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", "| No running processes found |\n", "+-----------------------------------------------------------------------------+\n" ] } ], "source": [ "!nvidia-smi" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 241, "referenced_widgets": [ "50a1252082d942b09bfc620a9fa9d1d0", "e270b7c82f784ebbbba4b17fb07c310d", "32eb83bb6fd34c56bb345368e47e8f6f", "34417f648cd54ed5b6d91f53af3e2713", "7518572223ac480b89af2ab71f38b2ed", "ce8bb7d0fb744e7b9ce2ff35cfdbc679", "aa47a09bf444413ba95322d979c1908c", "0b83a8775ea1441980d8ba945be752fe", "127389ec566e423ab9a8f60a9d61caaa", "4e4bc5550505497ba35f6bd7dde2893f", "e5124c5171e04625b70795e4b7a18819", "e410e7aecf23433f880a0f7169a8ce97", "0f6b3cf1d33f46f594934874170bcd83", "e549178ba75f4939aba6ae1cf743722a", "9c28978adf974326a21259ae56f47fe9", "7d3231a0b7794b11af662170b352d9e0" ] }, "id": "3Wj2W4tWcSeR", "outputId": "ad4eb63f-d643-45bd-b8d7-6adfefd9f773" }, "outputs": [ { "name": "stdout", "output_type": "stream", "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", "execution_count": 8, "metadata": { "id": "wHpUxFQPeWE2" }, "outputs": [], "source": [ "%%capture\n", "!apt install git-lfs" ] }, { "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": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "fevoJD15u4Ss", "outputId": "64745ecf-65b0-494d-a88d-52826eaae0f8" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2022-01-28 09:12:30-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/research_projects/robust-speech-event/run_speech_recognition_ctc_bnb.py\n", "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.109.133, ...\n", "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 31209 (30K) [text/plain]\n", "Saving to: ‘run_speech_recognition_ctc.py’\n", "\n", "run_speech_recognit 100%[===================>] 30.48K --.-KB/s in 0.001s \n", "\n", "2022-01-28 09:12:30 (21.4 MB/s) - ‘run_speech_recognition_ctc.py’ saved [31209/31209]\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\n", "# !wget -O run_speech_recognition_ctc.py https://raw.githubusercontent.com/huggingface/transformers/master/examples/research_projects/robust-speech-event/run_speech_recognition_ctc_bnb.py" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "id": "XJRA51HjcSeT" }, "outputs": [], "source": [ "# \t--learning_rate=\"7.5e-5\" \\\n", "# 84.5" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "hZOB6ZAnsvDX", "outputId": "7b6a85b5-950c-46a1-c005-b885f8a9bd17" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "nvcc: NVIDIA (R) Cuda compiler driver\n", "Copyright (c) 2005-2020 NVIDIA Corporation\n", "Built on Mon_Oct_12_20:09:46_PDT_2020\n", "Cuda compilation tools, release 11.1, V11.1.105\n", "Build cuda_11.1.TC455_06.29190527_0\n" ] } ], "source": [ "!nvcc --version" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "NKlgW0E-sldT", "outputId": "b925521a-29d2-4787-dd5b-6520dda688e4" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting bitsandbytes-cuda111\n", " Downloading bitsandbytes_cuda111-0.26.0-py3-none-any.whl (4.0 MB)\n", "\u001b[K |████████████████████████████████| 4.0 MB 4.3 MB/s \n", "\u001b[?25hInstalling collected packages: bitsandbytes-cuda111\n", "Successfully installed bitsandbytes-cuda111-0.26.0\n" ] } ], "source": [ "!pip install bitsandbytes-cuda111" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "remove special characters from datasets: 100%|█| 1010/1010 [00:00<00:00, 2695.96\n", "remove special characters from datasets: 100%|█| 421/421 [00:00<00:00, 7265.84ex\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, 17.05ba/s]\n", "100%|█████████████████████████████████████████████| 1/1 [00:00<00:00, 59.29ba/s]\n", "Didn't find file ./wav2vec2-large-xls-r-300m-romansh-vallader/tokenizer_config.json. We won't load it.\n", "Didn't find file ./wav2vec2-large-xls-r-300m-romansh-vallader/added_tokens.json. We won't load it.\n", "Didn't find file ./wav2vec2-large-xls-r-300m-romansh-vallader/special_tokens_map.json. We won't load it.\n", "Didn't find file ./wav2vec2-large-xls-r-300m-romansh-vallader/tokenizer.json. We won't load it.\n", "loading file ./wav2vec2-large-xls-r-300m-romansh-vallader/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-romansh-vallader/config.json not found\n", "Adding <s> to the vocabulary\n", "Adding </s> 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: ['project_hid.bias', 'quantizer.codevectors', 'project_q.weight', 'project_q.bias', 'quantizer.weight_proj.weight', 'project_hid.weight', '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: 100%|██████████████████| 1010/1010 [00:12<00:00, 78.52ex/s]\n", "preprocess datasets: 100%|████████████████████| 421/421 [00:04<00:00, 91.31ex/s]\n", "100%|████████████████████████████████████████████| 2/2 [00:00<00:00, 980.21ba/s]\n", "100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 866.41ba/s]\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "tokenizer config file saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/tokenizer_config.json\n", "Special tokens file saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/special_tokens_map.json\n", "added tokens file saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/added_tokens.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/config.json\n", "loading feature extractor configuration file ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "loading configuration file ./wav2vec2-large-xls-r-300m-romansh-vallader/config.json\n", "Model config Wav2Vec2Config {\n", " \"_name_or_path\": \"./wav2vec2-large-xls-r-300m-romansh-vallader\",\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-romansh-vallader/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-romansh-vallader/tokenizer.json. We won't load it.\n", "loading file ./wav2vec2-large-xls-r-300m-romansh-vallader/vocab.json\n", "loading file ./wav2vec2-large-xls-r-300m-romansh-vallader/tokenizer_config.json\n", "loading file ./wav2vec2-large-xls-r-300m-romansh-vallader/added_tokens.json\n", "loading file ./wav2vec2-large-xls-r-300m-romansh-vallader/special_tokens_map.json\n", "loading file None\n", "Adding <s> to the vocabulary\n", "Adding </s> to the vocabulary\n", "Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-vallader 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 = 1010\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 = 3200\n", " 16%|█████▉ | 500/3200 [18:48<1:31:12, 2.03s/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 = 421\n", " Batch size = 1\n", "\n", " 0%| | 0/421 [00:00<?, ?it/s]\u001b[A\n", " 1%|▎ | 3/421 [00:00<00:17, 23.24it/s]\u001b[A\n", " 1%|▌ | 6/421 [00:00<00:23, 18.01it/s]\u001b[A\n", " 2%|▊ | 8/421 [00:00<00:25, 16.18it/s]\u001b[A\n", " 2%|▉ | 10/421 [00:00<00:25, 16.34it/s]\u001b[A\n", " 3%|█▏ | 12/421 [00:00<00:24, 16.68it/s]\u001b[A\n", " 3%|█▍ | 14/421 [00:00<00:24, 16.70it/s]\u001b[A\n", " 4%|█▌ | 16/421 [00:00<00:24, 16.78it/s]\u001b[A\n", " 5%|█▉ | 19/421 [00:01<00:22, 17.77it/s]\u001b[A\n", " 5%|██▏ | 22/421 [00:01<00:21, 18.35it/s]\u001b[A\n", " 6%|██▍ | 24/421 [00:01<00:21, 18.13it/s]\u001b[A\n", " 6%|██▌ | 26/421 [00:01<00:21, 18.49it/s]\u001b[A\n", " 7%|██▊ | 28/421 [00:01<00:20, 18.80it/s]\u001b[A\n", " 7%|██▉ | 30/421 [00:01<00:21, 18.32it/s]\u001b[A\n", " 8%|███▏ | 32/421 [00:01<00:21, 17.87it/s]\u001b[A\n", " 8%|███▍ | 34/421 [00:01<00:22, 17.17it/s]\u001b[A\n", " 9%|███▌ | 36/421 [00:02<00:22, 16.97it/s]\u001b[A\n", " 9%|███▊ | 38/421 [00:02<00:22, 16.85it/s]\u001b[A\n", " 10%|███▉ | 40/421 [00:02<00:22, 16.83it/s]\u001b[A\n", " 10%|████▏ | 42/421 [00:02<00:23, 16.36it/s]\u001b[A\n", " 10%|████▍ | 44/421 [00:02<00:22, 16.47it/s]\u001b[A\n", " 11%|████▌ | 46/421 [00:02<00:22, 16.50it/s]\u001b[A\n", " 11%|████▊ | 48/421 [00:02<00:22, 16.89it/s]\u001b[A\n", " 12%|█████ | 51/421 [00:02<00:20, 18.26it/s]\u001b[A\n", " 13%|█████▎ | 53/421 [00:03<00:19, 18.48it/s]\u001b[A\n", " 13%|█████▍ | 55/421 [00:03<00:20, 17.93it/s]\u001b[A\n", " 14%|█████▋ | 57/421 [00:03<00:21, 17.26it/s]\u001b[A\n", " 14%|█████▉ | 60/421 [00:03<00:19, 18.29it/s]\u001b[A\n", " 15%|██████▏ | 62/421 [00:03<00:19, 18.44it/s]\u001b[A\n", " 15%|██████▍ | 64/421 [00:03<00:19, 18.04it/s]\u001b[A\n", " 16%|██████▌ | 66/421 [00:03<00:20, 17.49it/s]\u001b[A\n", " 16%|██████▊ | 68/421 [00:03<00:21, 16.70it/s]\u001b[A\n", " 17%|██████▉ | 70/421 [00:04<00:20, 17.11it/s]\u001b[A\n", " 17%|███████▏ | 72/421 [00:04<00:20, 17.20it/s]\u001b[A\n", " 18%|███████▍ | 74/421 [00:04<00:19, 17.50it/s]\u001b[A\n", " 18%|███████▋ | 77/421 [00:04<00:18, 18.42it/s]\u001b[A\n", " 19%|███████▉ | 79/421 [00:04<00:19, 17.77it/s]\u001b[A\n", " 19%|████████ | 81/421 [00:04<00:19, 17.36it/s]\u001b[A\n", " 20%|████████▎ | 83/421 [00:04<00:19, 17.37it/s]\u001b[A\n", " 20%|████████▍ | 85/421 [00:04<00:18, 17.77it/s]\u001b[A\n", " 21%|████████▋ | 87/421 [00:04<00:20, 16.53it/s]\u001b[A\n", " 21%|████████▉ | 89/421 [00:05<00:19, 17.02it/s]\u001b[A\n", " 22%|█████████ | 91/421 [00:05<00:19, 16.74it/s]\u001b[A\n", " 22%|█████████▎ | 93/421 [00:05<00:21, 15.58it/s]\u001b[A\n", " 23%|█████████▍ | 95/421 [00:05<00:20, 15.93it/s]\u001b[A\n", " 23%|█████████▋ | 97/421 [00:05<00:19, 16.24it/s]\u001b[A\n", " 24%|█████████▉ | 99/421 [00:05<00:20, 15.78it/s]\u001b[A\n", " 24%|█████████▊ | 101/421 [00:05<00:20, 15.47it/s]\u001b[A\n", " 24%|██████████ | 103/421 [00:06<00:20, 15.64it/s]\u001b[A\n", " 25%|██████████▏ | 105/421 [00:06<00:20, 15.41it/s]\u001b[A\n", " 25%|██████████▍ | 107/421 [00:06<00:19, 16.46it/s]\u001b[A\n", " 26%|██████████▌ | 109/421 [00:06<00:19, 16.11it/s]\u001b[A\n", " 26%|██████████▊ | 111/421 [00:06<00:20, 15.37it/s]\u001b[A\n", " 27%|███████████ | 113/421 [00:06<00:21, 14.33it/s]\u001b[A\n", " 27%|███████████▏ | 115/421 [00:06<00:21, 14.18it/s]\u001b[A\n", " 28%|███████████▍ | 117/421 [00:06<00:20, 14.84it/s]\u001b[A\n", " 28%|███████████▌ | 119/421 [00:07<00:19, 15.13it/s]\u001b[A\n", " 29%|███████████▊ | 121/421 [00:07<00:18, 15.81it/s]\u001b[A\n", " 29%|███████████▉ | 123/421 [00:07<00:19, 15.66it/s]\u001b[A\n", " 30%|████████████▏ | 125/421 [00:07<00:18, 16.06it/s]\u001b[A\n", " 30%|████████████▎ | 127/421 [00:07<00:18, 15.58it/s]\u001b[A\n", " 31%|████████████▌ | 129/421 [00:07<00:17, 16.25it/s]\u001b[A\n", " 31%|████████████▊ | 131/421 [00:07<00:18, 15.76it/s]\u001b[A\n", " 32%|████████████▉ | 133/421 [00:07<00:18, 15.28it/s]\u001b[A\n", " 32%|█████████████▏ | 135/421 [00:08<00:17, 16.10it/s]\u001b[A\n", " 33%|█████████████▎ | 137/421 [00:08<00:18, 15.60it/s]\u001b[A\n", " 33%|█████████████▌ | 139/421 [00:08<00:17, 16.07it/s]\u001b[A\n", " 33%|█████████████▋ | 141/421 [00:08<00:17, 15.71it/s]\u001b[A\n", " 34%|█████████████▉ | 143/421 [00:08<00:17, 15.54it/s]\u001b[A\n", " 34%|██████████████ | 145/421 [00:08<00:17, 16.14it/s]\u001b[A\n", " 35%|██████████████▎ | 147/421 [00:08<00:17, 15.76it/s]\u001b[A\n", " 35%|██████████████▌ | 149/421 [00:08<00:18, 15.09it/s]\u001b[A\n", " 36%|██████████████▋ | 151/421 [00:09<00:18, 14.99it/s]\u001b[A\n", " 36%|██████████████▉ | 153/421 [00:09<00:17, 15.39it/s]\u001b[A\n", " 37%|███████████████ | 155/421 [00:09<00:18, 14.65it/s]\u001b[A\n", " 37%|███████████████▎ | 157/421 [00:09<00:17, 14.94it/s]\u001b[A\n", " 38%|███████████████▍ | 159/421 [00:09<00:16, 15.63it/s]\u001b[A\n", " 38%|███████████████▋ | 161/421 [00:09<00:16, 15.85it/s]\u001b[A\n", " 39%|███████████████▊ | 163/421 [00:09<00:17, 14.41it/s]\u001b[A\n", " 39%|████████████████ | 165/421 [00:10<00:17, 14.83it/s]\u001b[A\n", " 40%|████████████████▎ | 167/421 [00:10<00:16, 15.30it/s]\u001b[A\n", " 40%|████████████████▍ | 169/421 [00:10<00:16, 15.57it/s]\u001b[A\n", " 41%|████████████████▋ | 171/421 [00:10<00:15, 15.67it/s]\u001b[A\n", " 41%|████████████████▊ | 173/421 [00:10<00:15, 15.88it/s]\u001b[A\n", " 42%|█████████████████ | 175/421 [00:10<00:14, 16.48it/s]\u001b[A\n", " 42%|█████████████████▏ | 177/421 [00:10<00:14, 16.88it/s]\u001b[A\n", " 43%|█████████████████▍ | 179/421 [00:10<00:15, 16.07it/s]\u001b[A\n", " 43%|█████████████████▋ | 181/421 [00:11<00:14, 16.42it/s]\u001b[A\n", " 44%|█████████████████▉ | 184/421 [00:11<00:13, 17.64it/s]\u001b[A\n", " 44%|██████████████████ | 186/421 [00:11<00:13, 17.30it/s]\u001b[A\n", " 45%|██████████████████▎ | 188/421 [00:11<00:13, 17.15it/s]\u001b[A\n", " 45%|██████████████████▌ | 190/421 [00:11<00:13, 17.06it/s]\u001b[A\n", " 46%|██████████████████▋ | 192/421 [00:11<00:13, 16.53it/s]\u001b[A\n", " 46%|██████████████████▉ | 194/421 [00:11<00:14, 16.03it/s]\u001b[A\n", " 47%|███████████████████ | 196/421 [00:11<00:13, 16.79it/s]\u001b[A\n", " 47%|███████████████████▎ | 198/421 [00:12<00:13, 16.92it/s]\u001b[A\n", " 48%|███████████████████▍ | 200/421 [00:12<00:13, 16.16it/s]\u001b[A\n", " 48%|███████████████████▋ | 202/421 [00:12<00:13, 16.32it/s]\u001b[A\n", " 48%|███████████████████▊ | 204/421 [00:12<00:13, 16.42it/s]\u001b[A\n", " 49%|████████████████████ | 206/421 [00:12<00:12, 16.74it/s]\u001b[A\n", " 49%|████████████████████▎ | 208/421 [00:12<00:13, 16.09it/s]\u001b[A\n", " 50%|████████████████████▍ | 210/421 [00:12<00:12, 16.43it/s]\u001b[A\n", " 50%|████████████████████▋ | 212/421 [00:12<00:12, 16.30it/s]\u001b[A\n", " 51%|████████████████████▊ | 214/421 [00:12<00:12, 16.09it/s]\u001b[A\n", " 52%|█████████████████████▏ | 217/421 [00:13<00:11, 17.40it/s]\u001b[A\n", " 52%|█████████████████████▎ | 219/421 [00:13<00:11, 16.87it/s]\u001b[A\n", " 52%|█████████████████████▌ | 221/421 [00:13<00:11, 16.87it/s]\u001b[A\n", " 53%|█████████████████████▋ | 223/421 [00:13<00:12, 16.39it/s]\u001b[A\n", " 53%|█████████████████████▉ | 225/421 [00:13<00:11, 16.36it/s]\u001b[A\n", " 54%|██████████████████████ | 227/421 [00:13<00:12, 15.85it/s]\u001b[A\n", " 54%|██████████████████████▎ | 229/421 [00:13<00:12, 15.39it/s]\u001b[A\n", " 55%|██████████████████████▍ | 231/421 [00:14<00:12, 15.00it/s]\u001b[A\n", " 55%|██████████████████████▋ | 233/421 [00:14<00:13, 14.31it/s]\u001b[A\n", " 56%|██████████████████████▉ | 235/421 [00:14<00:12, 14.78it/s]\u001b[A\n", " 56%|███████████████████████ | 237/421 [00:14<00:12, 15.10it/s]\u001b[A\n", " 57%|███████████████████████▎ | 239/421 [00:14<00:12, 14.65it/s]\u001b[A\n", " 57%|███████████████████████▍ | 241/421 [00:14<00:12, 14.95it/s]\u001b[A\n", " 58%|███████████████████████▋ | 243/421 [00:14<00:11, 15.62it/s]\u001b[A\n", " 58%|███████████████████████▊ | 245/421 [00:14<00:11, 15.64it/s]\u001b[A\n", " 59%|████████████████████████ | 247/421 [00:15<00:10, 15.92it/s]\u001b[A\n", " 59%|████████████████████████▏ | 249/421 [00:15<00:10, 16.15it/s]\u001b[A\n", " 60%|████████████████████████▍ | 251/421 [00:15<00:10, 15.89it/s]\u001b[A\n", " 60%|████████████████████████▋ | 253/421 [00:15<00:10, 15.62it/s]\u001b[A\n", " 61%|████████████████████████▊ | 255/421 [00:15<00:10, 15.19it/s]\u001b[A\n", " 61%|█████████████████████████▏ | 258/421 [00:15<00:09, 16.57it/s]\u001b[A\n", " 62%|█████████████████████████▎ | 260/421 [00:15<00:10, 16.05it/s]\u001b[A\n", " 62%|█████████████████████████▌ | 262/421 [00:16<00:10, 15.53it/s]\u001b[A\n", " 63%|█████████████████████████▋ | 264/421 [00:16<00:10, 15.24it/s]\u001b[A\n", " 63%|█████████████████████████▉ | 266/421 [00:16<00:10, 15.25it/s]\u001b[A\n", " 64%|██████████████████████████ | 268/421 [00:16<00:10, 14.88it/s]\u001b[A\n", " 64%|██████████████████████████▎ | 270/421 [00:16<00:09, 15.66it/s]\u001b[A\n", " 65%|██████████████████████████▍ | 272/421 [00:16<00:09, 16.17it/s]\u001b[A\n", " 65%|██████████████████████████▋ | 274/421 [00:16<00:08, 16.51it/s]\u001b[A\n", " 66%|██████████████████████████▉ | 276/421 [00:16<00:08, 17.26it/s]\u001b[A\n", " 66%|███████████████████████████ | 278/421 [00:17<00:08, 17.84it/s]\u001b[A\n", " 67%|███████████████████████████▎ | 280/421 [00:17<00:08, 16.65it/s]\u001b[A\n", " 67%|███████████████████████████▍ | 282/421 [00:17<00:08, 15.83it/s]\u001b[A\n", " 67%|███████████████████████████▋ | 284/421 [00:17<00:08, 15.27it/s]\u001b[A\n", " 68%|███████████████████████████▊ | 286/421 [00:17<00:08, 15.22it/s]\u001b[A\n", " 68%|████████████████████████████ | 288/421 [00:17<00:08, 16.00it/s]\u001b[A\n", " 69%|████████████████████████████▏ | 290/421 [00:17<00:07, 16.47it/s]\u001b[A\n", " 69%|████████████████████████████▍ | 292/421 [00:17<00:08, 15.85it/s]\u001b[A\n", " 70%|████████████████████████████▋ | 294/421 [00:18<00:07, 16.04it/s]\u001b[A\n", " 70%|████████████████████████████▊ | 296/421 [00:18<00:07, 16.02it/s]\u001b[A\n", " 71%|█████████████████████████████ | 298/421 [00:18<00:07, 16.35it/s]\u001b[A\n", " 71%|█████████████████████████████▏ | 300/421 [00:18<00:07, 15.89it/s]\u001b[A\n", " 72%|█████████████████████████████▍ | 302/421 [00:18<00:07, 16.08it/s]\u001b[A\n", " 72%|█████████████████████████████▌ | 304/421 [00:18<00:07, 15.78it/s]\u001b[A\n", " 73%|█████████████████████████████▊ | 306/421 [00:18<00:07, 15.56it/s]\u001b[A\n", " 73%|█████████████████████████████▉ | 308/421 [00:18<00:07, 14.40it/s]\u001b[A\n", " 74%|██████████████████████████████▏ | 310/421 [00:19<00:07, 15.69it/s]\u001b[A\n", " 74%|██████████████████████████████▍ | 312/421 [00:19<00:06, 16.02it/s]\u001b[A\n", " 75%|██████████████████████████████▌ | 314/421 [00:19<00:06, 16.91it/s]\u001b[A\n", " 75%|██████████████████████████████▊ | 316/421 [00:19<00:06, 16.94it/s]\u001b[A\n", " 76%|██████████████████████████████▉ | 318/421 [00:19<00:05, 17.62it/s]\u001b[A\n", " 76%|███████████████████████████████▏ | 320/421 [00:19<00:05, 17.59it/s]\u001b[A\n", " 76%|███████████████████████████████▎ | 322/421 [00:19<00:05, 17.02it/s]\u001b[A\n", " 77%|███████████████████████████████▌ | 324/421 [00:19<00:05, 17.00it/s]\u001b[A\n", " 77%|███████████████████████████████▋ | 326/421 [00:19<00:05, 17.07it/s]\u001b[A\n", " 78%|███████████████████████████████▉ | 328/421 [00:20<00:05, 16.48it/s]\u001b[A\n", " 78%|████████████████████████████████▏ | 330/421 [00:20<00:05, 16.95it/s]\u001b[A\n", " 79%|████████████████████████████████▎ | 332/421 [00:20<00:05, 16.55it/s]\u001b[A\n", " 79%|████████████████████████████████▌ | 334/421 [00:20<00:05, 16.39it/s]\u001b[A\n", " 80%|████████████████████████████████▋ | 336/421 [00:20<00:05, 16.49it/s]\u001b[A\n", " 80%|████████████████████████████████▉ | 338/421 [00:20<00:04, 16.83it/s]\u001b[A\n", " 81%|█████████████████████████████████ | 340/421 [00:20<00:05, 15.80it/s]\u001b[A\n", " 81%|█████████████████████████████████▎ | 342/421 [00:20<00:04, 16.17it/s]\u001b[A\n", " 82%|█████████████████████████████████▌ | 344/421 [00:21<00:04, 16.16it/s]\u001b[A\n", " 82%|█████████████████████████████████▋ | 346/421 [00:21<00:04, 16.18it/s]\u001b[A\n", " 83%|█████████████████████████████████▉ | 348/421 [00:21<00:04, 15.54it/s]\u001b[A\n", " 83%|██████████████████████████████████ | 350/421 [00:21<00:04, 15.48it/s]\u001b[A\n", " 84%|██████████████████████████████████▎ | 352/421 [00:21<00:04, 15.10it/s]\u001b[A\n", " 84%|██████████████████████████████████▍ | 354/421 [00:21<00:04, 14.23it/s]\u001b[A\n", " 85%|██████████████████████████████████▋ | 356/421 [00:21<00:04, 13.82it/s]\u001b[A\n", " 85%|██████████████████████████████████▊ | 358/421 [00:22<00:04, 13.37it/s]\u001b[A\n", " 86%|███████████████████████████████████ | 360/421 [00:22<00:04, 14.07it/s]\u001b[A\n", " 86%|███████████████████████████████████▎ | 362/421 [00:22<00:03, 15.08it/s]\u001b[A\n", " 86%|███████████████████████████████████▍ | 364/421 [00:22<00:03, 16.11it/s]\u001b[A\n", " 87%|███████████████████████████████████▋ | 366/421 [00:22<00:03, 16.05it/s]\u001b[A\n", " 87%|███████████████████████████████████▊ | 368/421 [00:22<00:03, 15.39it/s]\u001b[A\n", " 88%|████████████████████████████████████▏ | 371/421 [00:22<00:03, 16.38it/s]\u001b[A\n", " 89%|████████████████████████████████████▎ | 373/421 [00:23<00:02, 16.70it/s]\u001b[A\n", " 89%|████████████████████████████████████▌ | 375/421 [00:23<00:02, 16.45it/s]\u001b[A\n", " 90%|████████████████████████████████████▋ | 377/421 [00:23<00:02, 16.15it/s]\u001b[A\n", " 90%|████████████████████████████████████▉ | 379/421 [00:23<00:02, 16.89it/s]\u001b[A\n", " 90%|█████████████████████████████████████ | 381/421 [00:23<00:02, 15.97it/s]\u001b[A\n", " 91%|█████████████████████████████████████▎ | 383/421 [00:23<00:02, 15.06it/s]\u001b[A\n", " 91%|█████████████████████████████████████▍ | 385/421 [00:23<00:02, 14.89it/s]\u001b[A\n", " 92%|█████████████████████████████████████▋ | 387/421 [00:23<00:02, 15.07it/s]\u001b[A\n", " 92%|█████████████████████████████████████▉ | 389/421 [00:24<00:02, 15.42it/s]\u001b[A\n", " 93%|██████████████████████████████████████ | 391/421 [00:24<00:01, 15.24it/s]\u001b[A\n", " 93%|██████████████████████████████████████▎ | 393/421 [00:24<00:01, 15.01it/s]\u001b[A\n", " 94%|██████████████████████████████████████▍ | 395/421 [00:24<00:01, 14.95it/s]\u001b[A\n", " 94%|██████████████████████████████████████▋ | 397/421 [00:24<00:01, 15.62it/s]\u001b[A\n", " 95%|██████████████████████████████████████▊ | 399/421 [00:24<00:01, 15.66it/s]\u001b[A\n", " 95%|███████████████████████████████████████ | 401/421 [00:24<00:01, 16.38it/s]\u001b[A\n", " 96%|███████████████████████████████████████▏ | 403/421 [00:24<00:01, 16.55it/s]\u001b[A\n", " 96%|███████████████████████████████████████▍ | 405/421 [00:25<00:00, 16.63it/s]\u001b[A\n", " 97%|███████████████████████████████████████▋ | 407/421 [00:25<00:00, 17.06it/s]\u001b[A\n", " 97%|███████████████████████████████████████▊ | 409/421 [00:25<00:00, 16.90it/s]\u001b[A\n", " 98%|████████████████████████████████████████ | 411/421 [00:25<00:00, 17.24it/s]\u001b[A\n", " 98%|████████████████████████████████████████▎| 414/421 [00:25<00:00, 17.67it/s]\u001b[A\n", " 99%|████████████████████████████████████████▌| 416/421 [00:25<00:00, 16.59it/s]\u001b[A\n", " 99%|████████████████████████████████████████▋| 418/421 [00:25<00:00, 17.03it/s]\u001b[A\n", " \u001b[A\n", " 16%|█████▉ | 500/3200 [19:15<1:31:12, 2.03s/it]\n", "100%|█████████████████████████████████████████| 421/421 [00:26<00:00, 17.13it/s]\u001b[A\n", " \u001b[ASaving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-500\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-500/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-500/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-500/preprocessor_config.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", " 31%|███████████▌ | 1000/3200 [38:36<1:24:46, 2.31s/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 = 421\n", " Batch size = 1\n", "\n", " 0%| | 0/421 [00:00<?, ?it/s]\u001b[A\n", " 1%|▎ | 3/421 [00:00<00:17, 23.39it/s]\u001b[A\n", " 1%|▌ | 6/421 [00:00<00:23, 18.04it/s]\u001b[A\n", " 2%|▊ | 8/421 [00:00<00:25, 16.09it/s]\u001b[A\n", " 2%|▉ | 10/421 [00:00<00:25, 16.01it/s]\u001b[A\n", " 3%|█▏ | 12/421 [00:00<00:25, 16.34it/s]\u001b[A\n", " 3%|█▍ | 14/421 [00:00<00:24, 16.56it/s]\u001b[A\n", " 4%|█▌ | 16/421 [00:00<00:24, 16.57it/s]\u001b[A\n", " 5%|█▉ | 19/421 [00:01<00:22, 17.57it/s]\u001b[A\n", " 5%|██▏ | 22/421 [00:01<00:21, 18.34it/s]\u001b[A\n", " 6%|██▍ | 24/421 [00:01<00:21, 18.06it/s]\u001b[A\n", " 6%|██▌ | 26/421 [00:01<00:21, 18.37it/s]\u001b[A\n", " 7%|██▊ | 28/421 [00:01<00:21, 18.55it/s]\u001b[A\n", " 7%|██▉ | 30/421 [00:01<00:21, 17.81it/s]\u001b[A\n", " 8%|███▏ | 32/421 [00:01<00:22, 17.46it/s]\u001b[A\n", " 8%|███▍ | 34/421 [00:01<00:22, 16.95it/s]\u001b[A\n", " 9%|███▌ | 36/421 [00:02<00:23, 16.64it/s]\u001b[A\n", " 9%|███▊ | 38/421 [00:02<00:23, 16.59it/s]\u001b[A\n", " 10%|███▉ | 40/421 [00:02<00:23, 16.55it/s]\u001b[A\n", " 10%|████▏ | 42/421 [00:02<00:23, 16.18it/s]\u001b[A\n", " 10%|████▍ | 44/421 [00:02<00:23, 16.17it/s]\u001b[A\n", " 11%|████▌ | 46/421 [00:02<00:23, 16.25it/s]\u001b[A\n", " 11%|████▊ | 48/421 [00:02<00:22, 16.58it/s]\u001b[A\n", " 12%|█████ | 51/421 [00:02<00:20, 17.98it/s]\u001b[A\n", " 13%|█████▎ | 53/421 [00:03<00:20, 18.08it/s]\u001b[A\n", " 13%|█████▍ | 55/421 [00:03<00:20, 17.53it/s]\u001b[A\n", " 14%|█████▋ | 57/421 [00:03<00:22, 15.88it/s]\u001b[A\n", " 14%|█████▉ | 60/421 [00:03<00:20, 17.32it/s]\u001b[A\n", " 15%|██████▏ | 62/421 [00:03<00:20, 17.71it/s]\u001b[A\n", " 15%|██████▍ | 64/421 [00:03<00:20, 17.66it/s]\u001b[A\n", " 16%|██████▌ | 66/421 [00:03<00:21, 16.82it/s]\u001b[A\n", " 16%|██████▊ | 68/421 [00:03<00:22, 15.77it/s]\u001b[A\n", " 17%|██████▉ | 70/421 [00:04<00:21, 16.49it/s]\u001b[A\n", " 17%|███████▏ | 72/421 [00:04<00:20, 16.82it/s]\u001b[A\n", " 18%|███████▍ | 74/421 [00:04<00:20, 17.14it/s]\u001b[A\n", " 18%|███████▋ | 77/421 [00:04<00:19, 17.65it/s]\u001b[A\n", " 19%|███████▉ | 79/421 [00:04<00:20, 16.94it/s]\u001b[A\n", " 19%|████████ | 81/421 [00:04<00:21, 15.90it/s]\u001b[A\n", " 20%|████████▎ | 83/421 [00:04<00:21, 15.82it/s]\u001b[A\n", " 20%|████████▍ | 85/421 [00:04<00:20, 16.45it/s]\u001b[A\n", " 21%|████████▋ | 87/421 [00:05<00:21, 15.62it/s]\u001b[A\n", " 21%|████████▉ | 89/421 [00:05<00:20, 16.13it/s]\u001b[A\n", " 22%|█████████ | 91/421 [00:05<00:19, 16.54it/s]\u001b[A\n", " 22%|█████████▎ | 93/421 [00:05<00:21, 15.25it/s]\u001b[A\n", " 23%|█████████▍ | 95/421 [00:05<00:20, 15.62it/s]\u001b[A\n", " 23%|█████████▋ | 97/421 [00:05<00:20, 15.85it/s]\u001b[A\n", " 24%|█████████▉ | 99/421 [00:05<00:20, 15.44it/s]\u001b[A\n", " 24%|█████████▊ | 101/421 [00:06<00:21, 15.24it/s]\u001b[A\n", " 24%|██████████ | 103/421 [00:06<00:21, 15.07it/s]\u001b[A\n", " 25%|██████████▏ | 105/421 [00:06<00:21, 14.92it/s]\u001b[A\n", " 25%|██████████▍ | 107/421 [00:06<00:19, 16.11it/s]\u001b[A\n", " 26%|██████████▌ | 109/421 [00:06<00:19, 15.84it/s]\u001b[A\n", " 26%|██████████▊ | 111/421 [00:06<00:20, 15.29it/s]\u001b[A\n", " 27%|███████████ | 113/421 [00:06<00:21, 14.41it/s]\u001b[A\n", " 27%|███████████▏ | 115/421 [00:06<00:21, 14.18it/s]\u001b[A\n", " 28%|███████████▍ | 117/421 [00:07<00:20, 15.07it/s]\u001b[A\n", " 28%|███████████▌ | 119/421 [00:07<00:19, 15.13it/s]\u001b[A\n", " 29%|███████████▊ | 121/421 [00:07<00:19, 15.58it/s]\u001b[A\n", " 29%|███████████▉ | 123/421 [00:07<00:19, 15.33it/s]\u001b[A\n", " 30%|████████████▏ | 125/421 [00:07<00:18, 15.65it/s]\u001b[A\n", " 30%|████████████▎ | 127/421 [00:07<00:19, 15.21it/s]\u001b[A\n", " 31%|████████████▌ | 129/421 [00:07<00:18, 15.94it/s]\u001b[A\n", " 31%|████████████▊ | 131/421 [00:07<00:18, 15.62it/s]\u001b[A\n", " 32%|████████████▉ | 133/421 [00:08<00:19, 15.14it/s]\u001b[A\n", " 32%|█████████████▏ | 135/421 [00:08<00:18, 15.70it/s]\u001b[A\n", " 33%|█████████████▎ | 137/421 [00:08<00:18, 15.43it/s]\u001b[A\n", " 33%|█████████████▌ | 139/421 [00:08<00:17, 15.71it/s]\u001b[A\n", " 33%|█████████████▋ | 141/421 [00:08<00:18, 15.19it/s]\u001b[A\n", " 34%|█████████████▉ | 143/421 [00:08<00:18, 15.07it/s]\u001b[A\n", " 34%|██████████████ | 145/421 [00:08<00:17, 15.55it/s]\u001b[A\n", " 35%|██████████████▎ | 147/421 [00:09<00:17, 15.62it/s]\u001b[A\n", " 35%|██████████████▌ | 149/421 [00:09<00:17, 15.22it/s]\u001b[A\n", " 36%|██████████████▋ | 151/421 [00:09<00:18, 14.87it/s]\u001b[A\n", " 36%|██████████████▉ | 153/421 [00:09<00:17, 15.45it/s]\u001b[A\n", " 37%|███████████████ | 155/421 [00:09<00:18, 14.65it/s]\u001b[A\n", " 37%|███████████████▎ | 157/421 [00:09<00:17, 14.94it/s]\u001b[A\n", " 38%|███████████████▍ | 159/421 [00:09<00:17, 15.10it/s]\u001b[A\n", " 38%|███████████████▋ | 161/421 [00:09<00:16, 15.59it/s]\u001b[A\n", " 39%|███████████████▊ | 163/421 [00:10<00:18, 14.05it/s]\u001b[A\n", " 39%|████████████████ | 165/421 [00:10<00:18, 13.54it/s]\u001b[A\n", " 40%|████████████████▎ | 167/421 [00:10<00:17, 14.25it/s]\u001b[A\n", " 40%|████████████████▍ | 169/421 [00:10<00:16, 14.91it/s]\u001b[A\n", " 41%|████████████████▋ | 171/421 [00:10<00:16, 15.04it/s]\u001b[A\n", " 41%|████████████████▊ | 173/421 [00:10<00:16, 15.41it/s]\u001b[A\n", " 42%|█████████████████ | 175/421 [00:10<00:15, 16.01it/s]\u001b[A\n", " 42%|█████████████████▏ | 177/421 [00:11<00:14, 16.61it/s]\u001b[A\n", " 43%|█████████████████▍ | 179/421 [00:11<00:15, 15.82it/s]\u001b[A\n", " 43%|█████████████████▋ | 181/421 [00:11<00:14, 16.24it/s]\u001b[A\n", " 44%|█████████████████▉ | 184/421 [00:11<00:13, 17.51it/s]\u001b[A\n", " 44%|██████████████████ | 186/421 [00:11<00:13, 17.00it/s]\u001b[A\n", " 45%|██████████████████▎ | 188/421 [00:11<00:13, 16.65it/s]\u001b[A\n", " 45%|██████████████████▌ | 190/421 [00:11<00:13, 16.51it/s]\u001b[A\n", " 46%|██████████████████▋ | 192/421 [00:11<00:14, 16.17it/s]\u001b[A\n", " 46%|██████████████████▉ | 194/421 [00:12<00:14, 16.13it/s]\u001b[A\n", " 47%|███████████████████ | 196/421 [00:12<00:13, 17.06it/s]\u001b[A\n", " 47%|███████████████████▎ | 198/421 [00:12<00:12, 17.40it/s]\u001b[A\n", " 48%|███████████████████▍ | 200/421 [00:12<00:13, 16.53it/s]\u001b[A\n", " 48%|███████████████████▋ | 202/421 [00:12<00:13, 16.65it/s]\u001b[A\n", " 48%|███████████████████▊ | 204/421 [00:12<00:13, 16.42it/s]\u001b[A\n", " 49%|████████████████████ | 206/421 [00:12<00:12, 16.73it/s]\u001b[A\n", " 49%|████████████████████▎ | 208/421 [00:12<00:13, 16.03it/s]\u001b[A\n", " 50%|████████████████████▍ | 210/421 [00:13<00:12, 16.24it/s]\u001b[A\n", " 50%|████████████████████▋ | 212/421 [00:13<00:12, 16.43it/s]\u001b[A\n", " 51%|████████████████████▊ | 214/421 [00:13<00:12, 16.29it/s]\u001b[A\n", " 52%|█████████████████████▏ | 217/421 [00:13<00:11, 17.61it/s]\u001b[A\n", " 52%|█████████████████████▎ | 219/421 [00:13<00:12, 16.78it/s]\u001b[A\n", " 52%|█████████████████████▌ | 221/421 [00:13<00:11, 16.70it/s]\u001b[A\n", " 53%|█████████████████████▋ | 223/421 [00:13<00:12, 16.16it/s]\u001b[A\n", " 53%|█████████████████████▉ | 225/421 [00:13<00:12, 16.26it/s]\u001b[A\n", " 54%|██████████████████████ | 227/421 [00:14<00:12, 15.71it/s]\u001b[A\n", " 54%|██████████████████████▎ | 229/421 [00:14<00:12, 15.68it/s]\u001b[A\n", " 55%|██████████████████████▍ | 231/421 [00:14<00:12, 15.31it/s]\u001b[A\n", " 55%|██████████████████████▋ | 233/421 [00:14<00:12, 14.77it/s]\u001b[A\n", " 56%|██████████████████████▉ | 235/421 [00:14<00:12, 15.09it/s]\u001b[A\n", " 56%|███████████████████████ | 237/421 [00:14<00:12, 15.25it/s]\u001b[A\n", " 57%|███████████████████████▎ | 239/421 [00:14<00:12, 15.00it/s]\u001b[A\n", " 57%|███████████████████████▍ | 241/421 [00:14<00:11, 15.27it/s]\u001b[A\n", " 58%|███████████████████████▋ | 243/421 [00:15<00:11, 15.89it/s]\u001b[A\n", " 58%|███████████████████████▊ | 245/421 [00:15<00:11, 15.86it/s]\u001b[A\n", " 59%|████████████████████████ | 247/421 [00:15<00:10, 16.23it/s]\u001b[A\n", " 59%|████████████████████████▏ | 249/421 [00:15<00:10, 16.56it/s]\u001b[A\n", " 60%|████████████████████████▍ | 251/421 [00:15<00:10, 16.06it/s]\u001b[A\n", " 60%|████████████████████████▋ | 253/421 [00:15<00:10, 16.02it/s]\u001b[A\n", " 61%|████████████████████████▊ | 255/421 [00:15<00:10, 15.59it/s]\u001b[A\n", " 61%|█████████████████████████▏ | 258/421 [00:16<00:09, 17.04it/s]\u001b[A\n", " 62%|█████████████████████████▎ | 260/421 [00:16<00:09, 16.53it/s]\u001b[A\n", " 62%|█████████████████████████▌ | 262/421 [00:16<00:09, 15.95it/s]\u001b[A\n", " 63%|█████████████████████████▋ | 264/421 [00:16<00:10, 15.57it/s]\u001b[A\n", " 63%|█████████████████████████▉ | 266/421 [00:16<00:10, 15.05it/s]\u001b[A\n", " 64%|██████████████████████████ | 268/421 [00:16<00:10, 14.47it/s]\u001b[A\n", " 64%|██████████████████████████▎ | 270/421 [00:16<00:09, 15.33it/s]\u001b[A\n", " 65%|██████████████████████████▍ | 272/421 [00:16<00:09, 15.60it/s]\u001b[A\n", " 65%|██████████████████████████▋ | 274/421 [00:17<00:09, 15.86it/s]\u001b[A\n", " 66%|██████████████████████████▉ | 277/421 [00:17<00:08, 17.43it/s]\u001b[A\n", " 66%|███████████████████████████▏ | 279/421 [00:17<00:08, 17.27it/s]\u001b[A\n", " 67%|███████████████████████████▎ | 281/421 [00:17<00:08, 16.38it/s]\u001b[A\n", " 67%|███████████████████████████▌ | 283/421 [00:17<00:08, 15.66it/s]\u001b[A\n", " 68%|███████████████████████████▊ | 285/421 [00:17<00:09, 14.68it/s]\u001b[A\n", " 68%|███████████████████████████▉ | 287/421 [00:17<00:08, 15.84it/s]\u001b[A\n", " 69%|████████████████████████████▏ | 289/421 [00:17<00:08, 16.09it/s]\u001b[A\n", " 69%|████████████████████████████▎ | 291/421 [00:18<00:07, 16.72it/s]\u001b[A\n", " 70%|████████████████████████████▌ | 293/421 [00:18<00:08, 15.99it/s]\u001b[A\n", " 70%|████████████████████████████▋ | 295/421 [00:18<00:08, 15.63it/s]\u001b[A\n", " 71%|████████████████████████████▉ | 297/421 [00:18<00:08, 15.02it/s]\u001b[A\n", " 71%|█████████████████████████████ | 299/421 [00:18<00:07, 15.38it/s]\u001b[A\n", " 71%|█████████████████████████████▎ | 301/421 [00:18<00:07, 15.11it/s]\u001b[A\n", " 72%|█████████████████████████████▌ | 303/421 [00:18<00:07, 15.09it/s]\u001b[A\n", " 72%|█████████████████████████████▋ | 305/421 [00:19<00:07, 15.78it/s]\u001b[A\n", " 73%|█████████████████████████████▉ | 307/421 [00:19<00:07, 15.38it/s]\u001b[A\n", " 73%|██████████████████████████████ | 309/421 [00:19<00:07, 14.96it/s]\u001b[A\n", " 74%|██████████████████████████████▎ | 311/421 [00:19<00:06, 15.99it/s]\u001b[A\n", " 74%|██████████████████████████████▍ | 313/421 [00:19<00:06, 16.28it/s]\u001b[A\n", " 75%|██████████████████████████████▋ | 315/421 [00:19<00:06, 16.25it/s]\u001b[A\n", " 75%|██████████████████████████████▊ | 317/421 [00:19<00:06, 16.81it/s]\u001b[A\n", " 76%|███████████████████████████████ | 319/421 [00:19<00:05, 17.11it/s]\u001b[A\n", " 76%|███████████████████████████████▎ | 321/421 [00:19<00:05, 17.09it/s]\u001b[A\n", " 77%|███████████████████████████████▍ | 323/421 [00:20<00:05, 16.54it/s]\u001b[A\n", " 77%|███████████████████████████████▋ | 325/421 [00:20<00:05, 16.77it/s]\u001b[A\n", " 78%|███████████████████████████████▊ | 327/421 [00:20<00:05, 17.09it/s]\u001b[A\n", " 78%|████████████████████████████████ | 329/421 [00:20<00:05, 16.28it/s]\u001b[A\n", " 79%|████████████████████████████████▏ | 331/421 [00:20<00:05, 16.57it/s]\u001b[A\n", " 79%|████████████████████████████████▍ | 333/421 [00:20<00:05, 16.12it/s]\u001b[A\n", " 80%|████████████████████████████████▌ | 335/421 [00:20<00:05, 16.28it/s]\u001b[A\n", " 80%|████████████████████████████████▊ | 337/421 [00:20<00:05, 16.24it/s]\u001b[A\n", " 81%|█████████████████████████████████ | 339/421 [00:21<00:05, 16.37it/s]\u001b[A\n", " 81%|█████████████████████████████████▏ | 341/421 [00:21<00:04, 16.13it/s]\u001b[A\n", " 81%|█████████████████████████████████▍ | 343/421 [00:21<00:04, 16.08it/s]\u001b[A\n", " 82%|█████████████████████████████████▌ | 345/421 [00:21<00:04, 16.23it/s]\u001b[A\n", " 82%|█████████████████████████████████▊ | 347/421 [00:21<00:04, 15.81it/s]\u001b[A\n", " 83%|█████████████████████████████████▉ | 349/421 [00:21<00:04, 15.53it/s]\u001b[A\n", " 83%|██████████████████████████████████▏ | 351/421 [00:21<00:04, 15.46it/s]\u001b[A\n", " 84%|██████████████████████████████████▍ | 353/421 [00:22<00:04, 14.24it/s]\u001b[A\n", " 84%|██████████████████████████████████▌ | 355/421 [00:22<00:04, 13.89it/s]\u001b[A\n", " 85%|██████████████████████████████████▊ | 357/421 [00:22<00:04, 13.35it/s]\u001b[A\n", " 85%|██████████████████████████████████▉ | 359/421 [00:22<00:04, 13.67it/s]\u001b[A\n", " 86%|███████████████████████████████████▏ | 361/421 [00:22<00:04, 14.54it/s]\u001b[A\n", " 86%|███████████████████████████████████▎ | 363/421 [00:22<00:03, 14.51it/s]\u001b[A\n", " 87%|███████████████████████████████████▌ | 365/421 [00:22<00:03, 15.49it/s]\u001b[A\n", " 87%|███████████████████████████████████▋ | 367/421 [00:22<00:03, 14.84it/s]\u001b[A\n", " 88%|███████████████████████████████████▉ | 369/421 [00:23<00:03, 15.15it/s]\u001b[A\n", " 88%|████████████████████████████████████▏ | 371/421 [00:23<00:03, 15.79it/s]\u001b[A\n", " 89%|████████████████████████████████████▎ | 373/421 [00:23<00:02, 16.42it/s]\u001b[A\n", " 89%|████████████████████████████████████▌ | 375/421 [00:23<00:02, 16.40it/s]\u001b[A\n", " 90%|████████████████████████████████████▋ | 377/421 [00:23<00:02, 15.58it/s]\u001b[A\n", " 90%|████████████████████████████████████▉ | 379/421 [00:23<00:02, 16.31it/s]\u001b[A\n", " 90%|█████████████████████████████████████ | 381/421 [00:23<00:02, 15.98it/s]\u001b[A\n", " 91%|█████████████████████████████████████▎ | 383/421 [00:24<00:02, 14.78it/s]\u001b[A\n", " 91%|█████████████████████████████████████▍ | 385/421 [00:24<00:02, 14.11it/s]\u001b[A\n", " 92%|█████████████████████████████████████▋ | 387/421 [00:24<00:02, 14.47it/s]\u001b[A\n", " 92%|█████████████████████████████████████▉ | 389/421 [00:24<00:02, 15.20it/s]\u001b[A\n", " 93%|██████████████████████████████████████ | 391/421 [00:24<00:02, 14.99it/s]\u001b[A\n", " 93%|██████████████████████████████████████▎ | 393/421 [00:24<00:01, 14.73it/s]\u001b[A\n", " 94%|██████████████████████████████████████▍ | 395/421 [00:24<00:01, 15.28it/s]\u001b[A\n", " 94%|██████████████████████████████████████▋ | 397/421 [00:24<00:01, 15.86it/s]\u001b[A\n", " 95%|██████████████████████████████████████▊ | 399/421 [00:25<00:01, 15.74it/s]\u001b[A\n", " 95%|███████████████████████████████████████ | 401/421 [00:25<00:01, 16.21it/s]\u001b[A\n", " 96%|███████████████████████████████████████▏ | 403/421 [00:25<00:01, 16.08it/s]\u001b[A\n", " 96%|███████████████████████████████████████▍ | 405/421 [00:25<00:00, 16.30it/s]\u001b[A\n", " 97%|███████████████████████████████████████▋ | 407/421 [00:25<00:00, 16.96it/s]\u001b[A\n", " 97%|███████████████████████████████████████▊ | 409/421 [00:25<00:00, 16.57it/s]\u001b[A\n", " 98%|████████████████████████████████████████ | 411/421 [00:25<00:00, 16.64it/s]\u001b[A\n", " 98%|████████████████████████████████████████▏| 413/421 [00:25<00:00, 17.41it/s]\u001b[A\n", " 99%|████████████████████████████████████████▍| 415/421 [00:26<00:00, 15.60it/s]\u001b[A\n", " 99%|████████████████████████████████████████▌| 417/421 [00:26<00:00, 15.97it/s]\u001b[A\n", "100%|████████████████████████████████████████▊| 419/421 [00:26<00:00, 16.83it/s]\u001b[A\n", " \u001b[A\n", " 31%|███████████▌ | 1000/3200 [39:02<1:24:46, 2.31s/it]\n", "100%|█████████████████████████████████████████| 421/421 [00:26<00:00, 16.29it/s]\u001b[A\n", " \u001b[ASaving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1000\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1000/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1000/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1000/preprocessor_config.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", " 47%|██████████████████▎ | 1500/3200 [59:17<52:27, 1.85s/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 = 421\n", " Batch size = 1\n", "\n", " 0%| | 0/421 [00:00<?, ?it/s]\u001b[A\n", " 1%|▎ | 3/421 [00:00<00:17, 23.39it/s]\u001b[A\n", " 1%|▌ | 6/421 [00:00<00:22, 18.25it/s]\u001b[A\n", " 2%|▊ | 8/421 [00:00<00:25, 16.29it/s]\u001b[A\n", " 2%|▉ | 10/421 [00:00<00:25, 16.30it/s]\u001b[A\n", " 3%|█▏ | 12/421 [00:00<00:24, 16.70it/s]\u001b[A\n", " 3%|█▍ | 14/421 [00:00<00:25, 16.13it/s]\u001b[A\n", " 4%|█▌ | 16/421 [00:00<00:25, 15.97it/s]\u001b[A\n", " 5%|█▉ | 19/421 [00:01<00:23, 17.22it/s]\u001b[A\n", " 5%|██▏ | 22/421 [00:01<00:21, 18.29it/s]\u001b[A\n", " 6%|██▍ | 24/421 [00:01<00:21, 18.06it/s]\u001b[A\n", " 6%|██▌ | 26/421 [00:01<00:21, 18.50it/s]\u001b[A\n", " 7%|██▊ | 28/421 [00:01<00:20, 18.81it/s]\u001b[A\n", " 7%|██▉ | 30/421 [00:01<00:21, 18.45it/s]\u001b[A\n", " 8%|███▏ | 32/421 [00:01<00:21, 17.84it/s]\u001b[A\n", " 8%|███▍ | 34/421 [00:01<00:22, 17.13it/s]\u001b[A\n", " 9%|███▌ | 36/421 [00:02<00:22, 16.82it/s]\u001b[A\n", " 9%|███▊ | 38/421 [00:02<00:22, 16.71it/s]\u001b[A\n", " 10%|███▉ | 40/421 [00:02<00:22, 16.60it/s]\u001b[A\n", " 10%|████▏ | 42/421 [00:02<00:23, 16.32it/s]\u001b[A\n", " 10%|████▍ | 44/421 [00:02<00:23, 16.38it/s]\u001b[A\n", " 11%|████▌ | 46/421 [00:02<00:22, 16.35it/s]\u001b[A\n", " 11%|████▊ | 48/421 [00:02<00:22, 16.85it/s]\u001b[A\n", " 12%|█████ | 51/421 [00:02<00:19, 18.54it/s]\u001b[A\n", " 13%|█████▎ | 53/421 [00:03<00:19, 18.86it/s]\u001b[A\n", " 13%|█████▍ | 55/421 [00:03<00:20, 18.11it/s]\u001b[A\n", " 14%|█████▋ | 57/421 [00:03<00:21, 17.31it/s]\u001b[A\n", " 14%|█████▉ | 60/421 [00:03<00:19, 18.14it/s]\u001b[A\n", " 15%|██████▏ | 62/421 [00:03<00:19, 18.33it/s]\u001b[A\n", " 15%|██████▍ | 64/421 [00:03<00:19, 18.24it/s]\u001b[A\n", " 16%|██████▌ | 66/421 [00:03<00:20, 17.60it/s]\u001b[A\n", " 16%|██████▊ | 68/421 [00:03<00:20, 17.38it/s]\u001b[A\n", " 17%|██████▉ | 70/421 [00:04<00:19, 17.66it/s]\u001b[A\n", " 17%|███████▏ | 72/421 [00:04<00:21, 16.02it/s]\u001b[A\n", " 18%|███████▍ | 74/421 [00:04<00:20, 16.68it/s]\u001b[A\n", " 18%|███████▋ | 77/421 [00:04<00:19, 17.70it/s]\u001b[A\n", " 19%|███████▉ | 79/421 [00:04<00:19, 17.16it/s]\u001b[A\n", " 19%|████████ | 81/421 [00:04<00:20, 16.83it/s]\u001b[A\n", " 20%|████████▎ | 83/421 [00:04<00:19, 17.00it/s]\u001b[A\n", " 20%|████████▍ | 85/421 [00:04<00:19, 17.48it/s]\u001b[A\n", " 21%|████████▋ | 87/421 [00:05<00:20, 16.69it/s]\u001b[A\n", " 21%|████████▉ | 89/421 [00:05<00:19, 17.25it/s]\u001b[A\n", " 22%|█████████ | 91/421 [00:05<00:18, 17.49it/s]\u001b[A\n", " 22%|█████████▎ | 93/421 [00:05<00:20, 16.30it/s]\u001b[A\n", " 23%|█████████▍ | 95/421 [00:05<00:19, 16.63it/s]\u001b[A\n", " 23%|█████████▋ | 97/421 [00:05<00:19, 16.78it/s]\u001b[A\n", " 24%|█████████▉ | 99/421 [00:05<00:19, 16.31it/s]\u001b[A\n", " 24%|█████████▊ | 101/421 [00:05<00:20, 15.90it/s]\u001b[A\n", " 24%|██████████ | 103/421 [00:05<00:19, 16.20it/s]\u001b[A\n", " 25%|██████████▏ | 105/421 [00:06<00:19, 15.90it/s]\u001b[A\n", " 25%|██████████▍ | 107/421 [00:06<00:18, 16.86it/s]\u001b[A\n", " 26%|██████████▌ | 109/421 [00:06<00:18, 16.45it/s]\u001b[A\n", " 26%|██████████▊ | 111/421 [00:06<00:19, 15.78it/s]\u001b[A\n", " 27%|███████████ | 113/421 [00:06<00:20, 14.86it/s]\u001b[A\n", " 27%|███████████▏ | 115/421 [00:06<00:21, 14.55it/s]\u001b[A\n", " 28%|███████████▍ | 117/421 [00:06<00:19, 15.50it/s]\u001b[A\n", " 28%|███████████▌ | 119/421 [00:07<00:19, 15.53it/s]\u001b[A\n", " 29%|███████████▊ | 121/421 [00:07<00:18, 16.12it/s]\u001b[A\n", " 29%|███████████▉ | 123/421 [00:07<00:18, 15.90it/s]\u001b[A\n", " 30%|████████████▏ | 125/421 [00:07<00:18, 16.21it/s]\u001b[A\n", " 30%|████████████▎ | 127/421 [00:07<00:19, 15.25it/s]\u001b[A\n", " 31%|████████████▌ | 129/421 [00:07<00:18, 16.10it/s]\u001b[A\n", " 31%|████████████▊ | 131/421 [00:07<00:18, 15.88it/s]\u001b[A\n", " 32%|████████████▉ | 133/421 [00:07<00:18, 15.50it/s]\u001b[A\n", " 32%|█████████████▏ | 135/421 [00:08<00:17, 16.15it/s]\u001b[A\n", " 33%|█████████████▎ | 137/421 [00:08<00:18, 15.60it/s]\u001b[A\n", " 33%|█████████████▌ | 139/421 [00:08<00:17, 16.04it/s]\u001b[A\n", " 33%|█████████████▋ | 141/421 [00:08<00:17, 15.72it/s]\u001b[A\n", " 34%|█████████████▉ | 143/421 [00:08<00:18, 15.21it/s]\u001b[A\n", " 34%|██████████████ | 145/421 [00:08<00:17, 15.62it/s]\u001b[A\n", " 35%|██████████████▎ | 147/421 [00:08<00:17, 15.74it/s]\u001b[A\n", " 35%|██████████████▌ | 149/421 [00:08<00:17, 15.42it/s]\u001b[A\n", " 36%|██████████████▋ | 151/421 [00:09<00:17, 15.23it/s]\u001b[A\n", " 36%|██████████████▉ | 153/421 [00:09<00:17, 15.69it/s]\u001b[A\n", " 37%|███████████████ | 155/421 [00:09<00:17, 14.87it/s]\u001b[A\n", " 37%|███████████████▎ | 157/421 [00:09<00:17, 15.02it/s]\u001b[A\n", " 38%|███████████████▍ | 159/421 [00:09<00:16, 15.79it/s]\u001b[A\n", " 38%|███████████████▋ | 161/421 [00:09<00:15, 16.49it/s]\u001b[A\n", " 39%|███████████████▊ | 163/421 [00:09<00:17, 15.02it/s]\u001b[A\n", " 39%|████████████████ | 165/421 [00:09<00:16, 15.44it/s]\u001b[A\n", " 40%|████████████████▎ | 167/421 [00:10<00:16, 15.70it/s]\u001b[A\n", " 40%|████████████████▍ | 169/421 [00:10<00:15, 16.05it/s]\u001b[A\n", " 41%|████████████████▋ | 171/421 [00:10<00:15, 15.97it/s]\u001b[A\n", " 41%|████████████████▊ | 173/421 [00:10<00:15, 15.83it/s]\u001b[A\n", " 42%|█████████████████ | 175/421 [00:10<00:15, 16.29it/s]\u001b[A\n", " 42%|█████████████████▏ | 177/421 [00:10<00:14, 16.70it/s]\u001b[A\n", " 43%|█████████████████▍ | 179/421 [00:10<00:15, 16.00it/s]\u001b[A\n", " 43%|█████████████████▋ | 181/421 [00:10<00:14, 16.52it/s]\u001b[A\n", " 44%|█████████████████▉ | 184/421 [00:11<00:13, 17.60it/s]\u001b[A\n", " 44%|██████████████████ | 186/421 [00:11<00:13, 17.69it/s]\u001b[A\n", " 45%|██████████████████▎ | 188/421 [00:11<00:13, 17.74it/s]\u001b[A\n", " 45%|██████████████████▌ | 190/421 [00:11<00:13, 17.51it/s]\u001b[A\n", " 46%|██████████████████▋ | 192/421 [00:11<00:13, 16.91it/s]\u001b[A\n", " 46%|██████████████████▉ | 194/421 [00:11<00:13, 16.73it/s]\u001b[A\n", " 47%|███████████████████ | 196/421 [00:11<00:12, 17.57it/s]\u001b[A\n", " 47%|███████████████████▎ | 198/421 [00:11<00:12, 17.72it/s]\u001b[A\n", " 48%|███████████████████▍ | 200/421 [00:12<00:13, 16.56it/s]\u001b[A\n", " 48%|███████████████████▋ | 202/421 [00:12<00:13, 16.70it/s]\u001b[A\n", " 48%|███████████████████▊ | 204/421 [00:12<00:13, 16.56it/s]\u001b[A\n", " 49%|████████████████████ | 206/421 [00:12<00:12, 16.90it/s]\u001b[A\n", " 49%|████████████████████▎ | 208/421 [00:12<00:13, 16.19it/s]\u001b[A\n", " 50%|████████████████████▍ | 210/421 [00:12<00:12, 16.45it/s]\u001b[A\n", " 50%|████████████████████▋ | 212/421 [00:12<00:12, 16.73it/s]\u001b[A\n", " 51%|████████████████████▊ | 214/421 [00:12<00:12, 16.63it/s]\u001b[A\n", " 52%|█████████████████████▏ | 217/421 [00:13<00:11, 17.90it/s]\u001b[A\n", " 52%|█████████████████████▎ | 219/421 [00:13<00:11, 17.32it/s]\u001b[A\n", " 52%|█████████████████████▌ | 221/421 [00:13<00:11, 17.17it/s]\u001b[A\n", " 53%|█████████████████████▋ | 223/421 [00:13<00:11, 16.67it/s]\u001b[A\n", " 53%|█████████████████████▉ | 225/421 [00:13<00:11, 16.58it/s]\u001b[A\n", " 54%|██████████████████████ | 227/421 [00:13<00:12, 16.08it/s]\u001b[A\n", " 54%|██████████████████████▎ | 229/421 [00:13<00:12, 15.82it/s]\u001b[A\n", " 55%|██████████████████████▍ | 231/421 [00:13<00:12, 15.46it/s]\u001b[A\n", " 55%|██████████████████████▋ | 233/421 [00:14<00:12, 14.79it/s]\u001b[A\n", " 56%|██████████████████████▉ | 235/421 [00:14<00:12, 15.14it/s]\u001b[A\n", " 56%|███████████████████████ | 237/421 [00:14<00:12, 15.32it/s]\u001b[A\n", " 57%|███████████████████████▎ | 239/421 [00:14<00:12, 15.10it/s]\u001b[A\n", " 57%|███████████████████████▍ | 241/421 [00:14<00:11, 15.22it/s]\u001b[A\n", " 58%|███████████████████████▋ | 243/421 [00:14<00:11, 15.98it/s]\u001b[A\n", " 58%|███████████████████████▊ | 245/421 [00:14<00:10, 16.12it/s]\u001b[A\n", " 59%|████████████████████████ | 247/421 [00:14<00:10, 16.45it/s]\u001b[A\n", " 59%|████████████████████████▏ | 249/421 [00:15<00:10, 16.69it/s]\u001b[A\n", " 60%|████████████████████████▍ | 251/421 [00:15<00:10, 16.41it/s]\u001b[A\n", " 60%|████████████████████████▋ | 253/421 [00:15<00:10, 16.32it/s]\u001b[A\n", " 61%|████████████████████████▊ | 255/421 [00:15<00:10, 15.82it/s]\u001b[A\n", " 61%|█████████████████████████▏ | 258/421 [00:15<00:09, 17.14it/s]\u001b[A\n", " 62%|█████████████████████████▎ | 260/421 [00:15<00:09, 16.77it/s]\u001b[A\n", " 62%|█████████████████████████▌ | 262/421 [00:15<00:10, 15.76it/s]\u001b[A\n", " 63%|█████████████████████████▋ | 264/421 [00:16<00:10, 15.41it/s]\u001b[A\n", " 63%|█████████████████████████▉ | 266/421 [00:16<00:10, 15.38it/s]\u001b[A\n", " 64%|██████████████████████████ | 268/421 [00:16<00:10, 14.73it/s]\u001b[A\n", " 64%|██████████████████████████▎ | 270/421 [00:16<00:09, 15.46it/s]\u001b[A\n", " 65%|██████████████████████████▍ | 272/421 [00:16<00:09, 15.88it/s]\u001b[A\n", " 65%|██████████████████████████▋ | 274/421 [00:16<00:09, 16.15it/s]\u001b[A\n", " 66%|██████████████████████████▉ | 276/421 [00:16<00:08, 16.99it/s]\u001b[A\n", " 66%|███████████████████████████ | 278/421 [00:16<00:08, 17.74it/s]\u001b[A\n", " 67%|███████████████████████████▎ | 280/421 [00:16<00:08, 16.68it/s]\u001b[A\n", " 67%|███████████████████████████▍ | 282/421 [00:17<00:08, 16.21it/s]\u001b[A\n", " 67%|███████████████████████████▋ | 284/421 [00:17<00:08, 15.59it/s]\u001b[A\n", " 68%|███████████████████████████▊ | 286/421 [00:17<00:08, 15.50it/s]\u001b[A\n", " 68%|████████████████████████████ | 288/421 [00:17<00:08, 16.08it/s]\u001b[A\n", " 69%|████████████████████████████▏ | 290/421 [00:17<00:07, 16.84it/s]\u001b[A\n", " 69%|████████████████████████████▍ | 292/421 [00:17<00:07, 16.50it/s]\u001b[A\n", " 70%|████████████████████████████▋ | 294/421 [00:17<00:07, 16.63it/s]\u001b[A\n", " 70%|████████████████████████████▊ | 296/421 [00:17<00:07, 16.59it/s]\u001b[A\n", " 71%|█████████████████████████████ | 298/421 [00:18<00:07, 16.81it/s]\u001b[A\n", " 71%|█████████████████████████████▏ | 300/421 [00:18<00:07, 16.30it/s]\u001b[A\n", " 72%|█████████████████████████████▍ | 302/421 [00:18<00:07, 16.34it/s]\u001b[A\n", " 72%|█████████████████████████████▌ | 304/421 [00:18<00:07, 15.78it/s]\u001b[A\n", " 73%|█████████████████████████████▊ | 306/421 [00:18<00:07, 15.94it/s]\u001b[A\n", " 73%|█████████████████████████████▉ | 308/421 [00:18<00:07, 15.24it/s]\u001b[A\n", " 74%|██████████████████████████████▎ | 311/421 [00:18<00:06, 16.62it/s]\u001b[A\n", " 74%|██████████████████████████████▍ | 313/421 [00:19<00:06, 16.97it/s]\u001b[A\n", " 75%|██████████████████████████████▋ | 315/421 [00:19<00:06, 17.40it/s]\u001b[A\n", " 75%|██████████████████████████████▊ | 317/421 [00:19<00:05, 17.97it/s]\u001b[A\n", " 76%|███████████████████████████████ | 319/421 [00:19<00:05, 17.95it/s]\u001b[A\n", " 76%|███████████████████████████████▎ | 321/421 [00:19<00:05, 17.83it/s]\u001b[A\n", " 77%|███████████████████████████████▍ | 323/421 [00:19<00:05, 17.08it/s]\u001b[A\n", " 77%|███████████████████████████████▋ | 325/421 [00:19<00:05, 17.33it/s]\u001b[A\n", " 78%|███████████████████████████████▊ | 327/421 [00:19<00:05, 17.52it/s]\u001b[A\n", " 78%|████████████████████████████████ | 329/421 [00:19<00:05, 16.72it/s]\u001b[A\n", " 79%|████████████████████████████████▏ | 331/421 [00:20<00:05, 17.16it/s]\u001b[A\n", " 79%|████████████████████████████████▍ | 333/421 [00:20<00:05, 17.07it/s]\u001b[A\n", " 80%|████████████████████████████████▌ | 335/421 [00:20<00:04, 17.24it/s]\u001b[A\n", " 80%|████████████████████████████████▊ | 337/421 [00:20<00:05, 16.72it/s]\u001b[A\n", " 81%|█████████████████████████████████ | 339/421 [00:20<00:04, 16.50it/s]\u001b[A\n", " 81%|█████████████████████████████████▏ | 341/421 [00:20<00:04, 16.29it/s]\u001b[A\n", " 81%|█████████████████████████████████▍ | 343/421 [00:20<00:04, 16.01it/s]\u001b[A\n", " 82%|█████████████████████████████████▌ | 345/421 [00:20<00:04, 16.33it/s]\u001b[A\n", " 82%|█████████████████████████████████▊ | 347/421 [00:21<00:04, 16.16it/s]\u001b[A\n", " 83%|█████████████████████████████████▉ | 349/421 [00:21<00:04, 15.93it/s]\u001b[A\n", " 83%|██████████████████████████████████▏ | 351/421 [00:21<00:04, 15.69it/s]\u001b[A\n", " 84%|██████████████████████████████████▍ | 353/421 [00:21<00:04, 14.58it/s]\u001b[A\n", " 84%|██████████████████████████████████▌ | 355/421 [00:21<00:04, 14.11it/s]\u001b[A\n", " 85%|██████████████████████████████████▊ | 357/421 [00:21<00:04, 13.44it/s]\u001b[A\n", " 85%|██████████████████████████████████▉ | 359/421 [00:21<00:04, 13.77it/s]\u001b[A\n", " 86%|███████████████████████████████████▏ | 361/421 [00:21<00:04, 14.92it/s]\u001b[A\n", " 86%|███████████████████████████████████▎ | 363/421 [00:22<00:03, 15.47it/s]\u001b[A\n", " 87%|███████████████████████████████████▌ | 365/421 [00:22<00:03, 16.21it/s]\u001b[A\n", " 87%|███████████████████████████████████▋ | 367/421 [00:22<00:03, 15.28it/s]\u001b[A\n", " 88%|███████████████████████████████████▉ | 369/421 [00:22<00:03, 15.87it/s]\u001b[A\n", " 88%|████████████████████████████████████▏ | 371/421 [00:22<00:03, 16.44it/s]\u001b[A\n", " 89%|████████████████████████████████████▎ | 373/421 [00:22<00:02, 16.94it/s]\u001b[A\n", " 89%|████████████████████████████████████▌ | 375/421 [00:22<00:02, 16.75it/s]\u001b[A\n", " 90%|████████████████████████████████████▋ | 377/421 [00:22<00:02, 16.51it/s]\u001b[A\n", " 90%|████████████████████████████████████▉ | 379/421 [00:23<00:02, 17.16it/s]\u001b[A\n", " 90%|█████████████████████████████████████ | 381/421 [00:23<00:02, 16.66it/s]\u001b[A\n", " 91%|█████████████████████████████████████▎ | 383/421 [00:23<00:02, 15.46it/s]\u001b[A\n", " 91%|█████████████████████████████████████▍ | 385/421 [00:23<00:02, 15.23it/s]\u001b[A\n", " 92%|█████████████████████████████████████▋ | 387/421 [00:23<00:02, 15.54it/s]\u001b[A\n", " 92%|█████████████████████████████████████▉ | 389/421 [00:23<00:01, 16.04it/s]\u001b[A\n", " 93%|██████████████████████████████████████ | 391/421 [00:23<00:01, 15.75it/s]\u001b[A\n", " 93%|██████████████████████████████████████▎ | 393/421 [00:23<00:01, 15.38it/s]\u001b[A\n", " 94%|██████████████████████████████████████▍ | 395/421 [00:24<00:01, 15.92it/s]\u001b[A\n", " 94%|██████████████████████████████████████▋ | 397/421 [00:24<00:01, 16.42it/s]\u001b[A\n", " 95%|██████████████████████████████████████▊ | 399/421 [00:24<00:01, 16.12it/s]\u001b[A\n", " 95%|███████████████████████████████████████ | 401/421 [00:24<00:01, 16.51it/s]\u001b[A\n", " 96%|███████████████████████████████████████▏ | 403/421 [00:24<00:01, 16.77it/s]\u001b[A\n", " 96%|███████████████████████████████████████▍ | 405/421 [00:24<00:00, 16.91it/s]\u001b[A\n", " 97%|███████████████████████████████████████▋ | 407/421 [00:24<00:00, 17.48it/s]\u001b[A\n", " 97%|███████████████████████████████████████▊ | 409/421 [00:24<00:00, 17.52it/s]\u001b[A\n", " 98%|████████████████████████████████████████ | 411/421 [00:25<00:00, 17.93it/s]\u001b[A\n", " 98%|████████████████████████████████████████▎| 414/421 [00:25<00:00, 18.24it/s]\u001b[A\n", " 99%|████████████████████████████████████████▌| 416/421 [00:25<00:00, 16.92it/s]\u001b[A\n", " 99%|████████████████████████████████████████▋| 418/421 [00:25<00:00, 17.19it/s]\u001b[A\n", " \u001b[A\n", " 47%|██████████████████▎ | 1500/3200 [59:43<52:27, 1.85s/it]\n", "100%|█████████████████████████████████████████| 421/421 [00:25<00:00, 17.37it/s]\u001b[A\n", " \u001b[ASaving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1500\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1500/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1500/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1500/preprocessor_config.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-500] due to args.save_total_limit\n", " 62%|███████████████████████ | 1992/3200 [1:19:54<47:32, 2.36s/it]Deleting older checkpoint [wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1000] due to args.save_total_limit\n", " 78%|████████████████████████████▉ | 2500/3200 [1:40:57<27:53, 2.39s/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 = 421\n", " Batch size = 1\n", "\n", " 0%| | 0/421 [00:00<?, ?it/s]\u001b[A\n", " 1%|▎ | 3/421 [00:00<00:22, 18.47it/s]\u001b[A\n", " 1%|▌ | 5/421 [00:00<00:27, 14.97it/s]\u001b[A\n", " 2%|▋ | 7/421 [00:00<00:31, 13.32it/s]\u001b[A\n", " 2%|▉ | 9/421 [00:00<00:32, 12.68it/s]\u001b[A\n", " 3%|█ | 11/421 [00:00<00:30, 13.46it/s]\u001b[A\n", " 3%|█▎ | 13/421 [00:00<00:31, 13.15it/s]\u001b[A\n", " 4%|█▍ | 15/421 [00:01<00:30, 13.39it/s]\u001b[A\n", " 4%|█▋ | 17/421 [00:01<00:28, 14.04it/s]\u001b[A\n", " 5%|█▉ | 19/421 [00:01<00:27, 14.63it/s]\u001b[A\n", " 5%|██ | 21/421 [00:01<00:26, 15.26it/s]\u001b[A\n", " 5%|██▎ | 23/421 [00:01<00:26, 15.12it/s]\u001b[A\n", " 6%|██▍ | 25/421 [00:01<00:26, 15.15it/s]\u001b[A\n", " 6%|██▋ | 27/421 [00:01<00:26, 15.01it/s]\u001b[A\n", " 7%|██▉ | 29/421 [00:01<00:25, 15.47it/s]\u001b[A\n", " 7%|███ | 31/421 [00:02<00:25, 15.04it/s]\u001b[A\n", " 8%|███▍ | 34/421 [00:02<00:24, 15.90it/s]\u001b[A\n", " 9%|███▌ | 36/421 [00:02<00:23, 16.11it/s]\u001b[A\n", " 9%|███▊ | 38/421 [00:02<00:23, 16.20it/s]\u001b[A\n", " 10%|███▉ | 40/421 [00:02<00:23, 16.32it/s]\u001b[A\n", " 10%|████▏ | 42/421 [00:02<00:23, 16.24it/s]\u001b[A\n", " 10%|████▍ | 44/421 [00:02<00:23, 16.29it/s]\u001b[A\n", " 11%|████▌ | 46/421 [00:03<00:22, 16.44it/s]\u001b[A\n", " 11%|████▊ | 48/421 [00:03<00:22, 16.91it/s]\u001b[A\n", " 12%|█████ | 51/421 [00:03<00:19, 18.59it/s]\u001b[A\n", " 13%|█████▎ | 53/421 [00:03<00:19, 18.89it/s]\u001b[A\n", " 13%|█████▍ | 55/421 [00:03<00:20, 18.20it/s]\u001b[A\n", " 14%|█████▋ | 57/421 [00:03<00:20, 17.36it/s]\u001b[A\n", " 14%|█████▉ | 60/421 [00:03<00:19, 18.35it/s]\u001b[A\n", " 15%|██████▏ | 62/421 [00:03<00:19, 18.46it/s]\u001b[A\n", " 15%|██████▍ | 64/421 [00:03<00:19, 18.21it/s]\u001b[A\n", " 16%|██████▌ | 66/421 [00:04<00:20, 17.52it/s]\u001b[A\n", " 16%|██████▊ | 68/421 [00:04<00:20, 17.22it/s]\u001b[A\n", " 17%|██████▉ | 70/421 [00:04<00:20, 17.41it/s]\u001b[A\n", " 17%|███████▏ | 72/421 [00:04<00:19, 17.56it/s]\u001b[A\n", " 18%|███████▍ | 74/421 [00:04<00:19, 17.70it/s]\u001b[A\n", " 18%|███████▋ | 77/421 [00:04<00:18, 18.22it/s]\u001b[A\n", " 19%|███████▉ | 79/421 [00:04<00:19, 17.59it/s]\u001b[A\n", " 19%|████████ | 81/421 [00:04<00:19, 17.13it/s]\u001b[A\n", " 20%|████████▎ | 83/421 [00:05<00:19, 17.12it/s]\u001b[A\n", " 20%|████████▍ | 85/421 [00:05<00:19, 17.56it/s]\u001b[A\n", " 21%|████████▋ | 87/421 [00:05<00:20, 16.68it/s]\u001b[A\n", " 21%|████████▉ | 89/421 [00:05<00:19, 16.75it/s]\u001b[A\n", " 22%|█████████ | 91/421 [00:05<00:19, 16.92it/s]\u001b[A\n", " 22%|█████████▎ | 93/421 [00:05<00:21, 15.12it/s]\u001b[A\n", " 23%|█████████▍ | 95/421 [00:05<00:20, 15.55it/s]\u001b[A\n", " 23%|█████████▋ | 97/421 [00:06<00:21, 15.19it/s]\u001b[A\n", " 24%|█████████▉ | 99/421 [00:06<00:21, 15.21it/s]\u001b[A\n", " 24%|█████████▊ | 101/421 [00:06<00:21, 15.13it/s]\u001b[A\n", " 24%|██████████ | 103/421 [00:06<00:20, 15.60it/s]\u001b[A\n", " 25%|██████████▏ | 105/421 [00:06<00:20, 15.42it/s]\u001b[A\n", " 25%|██████████▍ | 107/421 [00:06<00:19, 16.47it/s]\u001b[A\n", " 26%|██████████▌ | 109/421 [00:06<00:19, 16.21it/s]\u001b[A\n", " 26%|██████████▊ | 111/421 [00:06<00:19, 15.66it/s]\u001b[A\n", " 27%|███████████ | 113/421 [00:07<00:20, 14.70it/s]\u001b[A\n", " 27%|███████████▏ | 115/421 [00:07<00:21, 14.49it/s]\u001b[A\n", " 28%|███████████▍ | 117/421 [00:07<00:19, 15.48it/s]\u001b[A\n", " 28%|███████████▌ | 119/421 [00:07<00:19, 15.68it/s]\u001b[A\n", " 29%|███████████▊ | 121/421 [00:07<00:18, 16.16it/s]\u001b[A\n", " 29%|███████████▉ | 123/421 [00:07<00:18, 15.83it/s]\u001b[A\n", " 30%|████████████▏ | 125/421 [00:07<00:18, 16.24it/s]\u001b[A\n", " 30%|████████████▎ | 127/421 [00:07<00:18, 15.69it/s]\u001b[A\n", " 31%|████████████▌ | 129/421 [00:08<00:17, 16.43it/s]\u001b[A\n", " 31%|████████████▊ | 131/421 [00:08<00:17, 16.22it/s]\u001b[A\n", " 32%|████████████▉ | 133/421 [00:08<00:18, 15.54it/s]\u001b[A\n", " 32%|█████████████▏ | 135/421 [00:08<00:17, 16.26it/s]\u001b[A\n", " 33%|█████████████▎ | 137/421 [00:08<00:18, 15.72it/s]\u001b[A\n", " 33%|█████████████▌ | 139/421 [00:08<00:17, 16.05it/s]\u001b[A\n", " 33%|█████████████▋ | 141/421 [00:08<00:17, 15.63it/s]\u001b[A\n", " 34%|█████████████▉ | 143/421 [00:08<00:18, 15.26it/s]\u001b[A\n", " 34%|██████████████ | 145/421 [00:09<00:17, 16.05it/s]\u001b[A\n", " 35%|██████████████▎ | 147/421 [00:09<00:17, 16.06it/s]\u001b[A\n", " 35%|██████████████▌ | 149/421 [00:09<00:17, 15.59it/s]\u001b[A\n", " 36%|██████████████▋ | 151/421 [00:09<00:17, 15.19it/s]\u001b[A\n", " 36%|██████████████▉ | 153/421 [00:09<00:17, 15.64it/s]\u001b[A\n", " 37%|███████████████ | 155/421 [00:09<00:17, 14.84it/s]\u001b[A\n", " 37%|███████████████▎ | 157/421 [00:09<00:17, 15.10it/s]\u001b[A\n", " 38%|███████████████▍ | 159/421 [00:09<00:16, 15.89it/s]\u001b[A\n", " 38%|███████████████▋ | 161/421 [00:10<00:15, 16.62it/s]\u001b[A\n", " 39%|███████████████▊ | 163/421 [00:10<00:17, 14.93it/s]\u001b[A\n", " 39%|████████████████ | 165/421 [00:10<00:16, 15.23it/s]\u001b[A\n", " 40%|████████████████▎ | 167/421 [00:10<00:16, 15.36it/s]\u001b[A\n", " 40%|████████████████▍ | 169/421 [00:10<00:16, 15.28it/s]\u001b[A\n", " 41%|████████████████▋ | 171/421 [00:10<00:16, 14.98it/s]\u001b[A\n", " 41%|████████████████▊ | 173/421 [00:10<00:16, 14.90it/s]\u001b[A\n", " 42%|█████████████████ | 175/421 [00:10<00:15, 15.65it/s]\u001b[A\n", " 42%|█████████████████▏ | 177/421 [00:11<00:15, 16.09it/s]\u001b[A\n", " 43%|█████████████████▍ | 179/421 [00:11<00:15, 15.61it/s]\u001b[A\n", " 43%|█████████████████▋ | 181/421 [00:11<00:14, 16.21it/s]\u001b[A\n", " 44%|█████████████████▉ | 184/421 [00:11<00:13, 17.30it/s]\u001b[A\n", " 44%|██████████████████ | 186/421 [00:11<00:13, 17.32it/s]\u001b[A\n", " 45%|██████████████████▎ | 188/421 [00:11<00:13, 16.79it/s]\u001b[A\n", " 45%|██████████████████▌ | 190/421 [00:11<00:13, 16.82it/s]\u001b[A\n", " 46%|██████████████████▋ | 192/421 [00:12<00:14, 16.02it/s]\u001b[A\n", " 46%|██████████████████▉ | 194/421 [00:12<00:15, 14.81it/s]\u001b[A\n", " 47%|███████████████████ | 196/421 [00:12<00:14, 15.38it/s]\u001b[A\n", " 47%|███████████████████▎ | 198/421 [00:12<00:13, 16.11it/s]\u001b[A\n", " 48%|███████████████████▍ | 200/421 [00:12<00:14, 15.37it/s]\u001b[A\n", " 48%|███████████████████▋ | 202/421 [00:12<00:13, 15.73it/s]\u001b[A\n", " 48%|███████████████████▊ | 204/421 [00:12<00:13, 15.97it/s]\u001b[A\n", " 49%|████████████████████ | 206/421 [00:12<00:13, 16.44it/s]\u001b[A\n", " 49%|████████████████████▎ | 208/421 [00:13<00:13, 15.86it/s]\u001b[A\n", " 50%|████████████████████▍ | 210/421 [00:13<00:12, 16.35it/s]\u001b[A\n", " 50%|████████████████████▋ | 212/421 [00:13<00:12, 16.67it/s]\u001b[A\n", " 51%|████████████████████▊ | 214/421 [00:13<00:12, 16.50it/s]\u001b[A\n", " 51%|█████████████████████ | 216/421 [00:13<00:11, 17.36it/s]\u001b[A\n", " 52%|█████████████████████▏ | 218/421 [00:13<00:11, 17.14it/s]\u001b[A\n", " 52%|█████████████████████▍ | 220/421 [00:13<00:11, 16.98it/s]\u001b[A\n", " 53%|█████████████████████▌ | 222/421 [00:13<00:12, 16.54it/s]\u001b[A\n", " 53%|█████████████████████▊ | 224/421 [00:13<00:12, 16.12it/s]\u001b[A\n", " 54%|██████████████████████ | 226/421 [00:14<00:12, 15.83it/s]\u001b[A\n", " 54%|██████████████████████▏ | 228/421 [00:14<00:12, 16.06it/s]\u001b[A\n", " 55%|██████████████████████▍ | 230/421 [00:14<00:12, 15.75it/s]\u001b[A\n", " 55%|██████████████████████▌ | 232/421 [00:14<00:12, 15.07it/s]\u001b[A\n", " 56%|██████████████████████▊ | 234/421 [00:14<00:12, 15.01it/s]\u001b[A\n", " 56%|██████████████████████▉ | 236/421 [00:14<00:11, 15.57it/s]\u001b[A\n", " 57%|███████████████████████▏ | 238/421 [00:14<00:11, 15.26it/s]\u001b[A\n", " 57%|███████████████████████▎ | 240/421 [00:15<00:12, 15.05it/s]\u001b[A\n", " 57%|███████████████████████▌ | 242/421 [00:15<00:11, 15.50it/s]\u001b[A\n", " 58%|███████████████████████▊ | 244/421 [00:15<00:11, 15.94it/s]\u001b[A\n", " 58%|███████████████████████▉ | 246/421 [00:15<00:10, 15.97it/s]\u001b[A\n", " 59%|████████████████████████▏ | 248/421 [00:15<00:11, 15.51it/s]\u001b[A\n", " 59%|████████████████████████▎ | 250/421 [00:15<00:10, 15.65it/s]\u001b[A\n", " 60%|████████████████████████▌ | 252/421 [00:15<00:10, 16.07it/s]\u001b[A\n", " 60%|████████████████████████▋ | 254/421 [00:15<00:10, 15.85it/s]\u001b[A\n", " 61%|████████████████████████▉ | 256/421 [00:16<00:10, 16.14it/s]\u001b[A\n", " 61%|█████████████████████████▏ | 258/421 [00:16<00:09, 16.75it/s]\u001b[A\n", " 62%|█████████████████████████▎ | 260/421 [00:16<00:09, 16.46it/s]\u001b[A\n", " 62%|█████████████████████████▌ | 262/421 [00:16<00:10, 15.80it/s]\u001b[A\n", " 63%|█████████████████████████▋ | 264/421 [00:16<00:10, 15.17it/s]\u001b[A\n", " 63%|█████████████████████████▉ | 266/421 [00:16<00:10, 14.87it/s]\u001b[A\n", " 64%|██████████████████████████ | 268/421 [00:16<00:10, 14.60it/s]\u001b[A\n", " 64%|██████████████████████████▎ | 270/421 [00:16<00:09, 15.49it/s]\u001b[A\n", " 65%|██████████████████████████▍ | 272/421 [00:17<00:09, 15.86it/s]\u001b[A\n", " 65%|██████████████████████████▋ | 274/421 [00:17<00:09, 16.25it/s]\u001b[A\n", " 66%|██████████████████████████▉ | 277/421 [00:17<00:08, 17.90it/s]\u001b[A\n", " 66%|███████████████████████████▏ | 279/421 [00:17<00:07, 17.77it/s]\u001b[A\n", " 67%|███████████████████████████▎ | 281/421 [00:17<00:08, 16.64it/s]\u001b[A\n", " 67%|███████████████████████████▌ | 283/421 [00:17<00:08, 16.18it/s]\u001b[A\n", " 68%|███████████████████████████▊ | 285/421 [00:17<00:09, 15.07it/s]\u001b[A\n", " 68%|████████████████████████████ | 288/421 [00:18<00:08, 16.27it/s]\u001b[A\n", " 69%|████████████████████████████▏ | 290/421 [00:18<00:07, 16.83it/s]\u001b[A\n", " 69%|████████████████████████████▍ | 292/421 [00:18<00:07, 16.44it/s]\u001b[A\n", " 70%|████████████████████████████▋ | 294/421 [00:18<00:07, 16.56it/s]\u001b[A\n", " 70%|████████████████████████████▊ | 296/421 [00:18<00:07, 16.16it/s]\u001b[A\n", " 71%|█████████████████████████████ | 298/421 [00:18<00:07, 16.17it/s]\u001b[A\n", " 71%|█████████████████████████████▏ | 300/421 [00:18<00:07, 15.85it/s]\u001b[A\n", " 72%|█████████████████████████████▍ | 302/421 [00:18<00:07, 15.96it/s]\u001b[A\n", " 72%|█████████████████████████████▌ | 304/421 [00:19<00:07, 15.61it/s]\u001b[A\n", " 73%|█████████████████████████████▊ | 306/421 [00:19<00:07, 15.93it/s]\u001b[A\n", " 73%|█████████████████████████████▉ | 308/421 [00:19<00:07, 15.33it/s]\u001b[A\n", " 74%|██████████████████████████████▎ | 311/421 [00:19<00:06, 16.79it/s]\u001b[A\n", " 74%|██████████████████████████████▍ | 313/421 [00:19<00:06, 16.89it/s]\u001b[A\n", " 75%|██████████████████████████████▋ | 315/421 [00:19<00:06, 17.45it/s]\u001b[A\n", " 75%|██████████████████████████████▊ | 317/421 [00:19<00:05, 17.58it/s]\u001b[A\n", " 76%|███████████████████████████████ | 319/421 [00:19<00:05, 17.63it/s]\u001b[A\n", " 76%|███████████████████████████████▎ | 321/421 [00:20<00:05, 17.75it/s]\u001b[A\n", " 77%|███████████████████████████████▍ | 323/421 [00:20<00:05, 16.99it/s]\u001b[A\n", " 77%|███████████████████████████████▋ | 325/421 [00:20<00:05, 17.12it/s]\u001b[A\n", " 78%|███████████████████████████████▊ | 327/421 [00:20<00:05, 17.40it/s]\u001b[A\n", " 78%|████████████████████████████████ | 329/421 [00:20<00:05, 16.34it/s]\u001b[A\n", " 79%|████████████████████████████████▏ | 331/421 [00:20<00:05, 16.46it/s]\u001b[A\n", " 79%|████████████████████████████████▍ | 333/421 [00:20<00:05, 16.44it/s]\u001b[A\n", " 80%|████████████████████████████████▌ | 335/421 [00:20<00:05, 16.68it/s]\u001b[A\n", " 80%|████████████████████████████████▊ | 337/421 [00:20<00:05, 16.44it/s]\u001b[A\n", " 81%|█████████████████████████████████ | 339/421 [00:21<00:04, 16.41it/s]\u001b[A\n", " 81%|█████████████████████████████████▏ | 341/421 [00:21<00:04, 16.14it/s]\u001b[A\n", " 81%|█████████████████████████████████▍ | 343/421 [00:21<00:04, 16.01it/s]\u001b[A\n", " 82%|█████████████████████████████████▌ | 345/421 [00:21<00:04, 16.19it/s]\u001b[A\n", " 82%|█████████████████████████████████▊ | 347/421 [00:21<00:04, 15.94it/s]\u001b[A\n", " 83%|█████████████████████████████████▉ | 349/421 [00:21<00:04, 15.50it/s]\u001b[A\n", " 83%|██████████████████████████████████▏ | 351/421 [00:21<00:04, 15.12it/s]\u001b[A\n", " 84%|██████████████████████████████████▍ | 353/421 [00:22<00:04, 13.69it/s]\u001b[A\n", " 84%|██████████████████████████████████▌ | 355/421 [00:22<00:04, 13.41it/s]\u001b[A\n", " 85%|██████████████████████████████████▊ | 357/421 [00:22<00:04, 13.05it/s]\u001b[A\n", " 85%|██████████████████████████████████▉ | 359/421 [00:22<00:04, 13.36it/s]\u001b[A\n", " 86%|███████████████████████████████████▏ | 361/421 [00:22<00:04, 14.46it/s]\u001b[A\n", " 86%|███████████████████████████████████▎ | 363/421 [00:22<00:03, 15.06it/s]\u001b[A\n", " 87%|███████████████████████████████████▌ | 365/421 [00:22<00:03, 15.50it/s]\u001b[A\n", " 87%|███████████████████████████████████▋ | 367/421 [00:23<00:03, 15.03it/s]\u001b[A\n", " 88%|███████████████████████████████████▉ | 369/421 [00:23<00:03, 15.57it/s]\u001b[A\n", " 88%|████████████████████████████████████▏ | 371/421 [00:23<00:03, 15.96it/s]\u001b[A\n", " 89%|████████████████████████████████████▎ | 373/421 [00:23<00:02, 16.52it/s]\u001b[A\n", " 89%|████████████████████████████████████▌ | 375/421 [00:23<00:02, 16.23it/s]\u001b[A\n", " 90%|████████████████████████████████████▋ | 377/421 [00:23<00:02, 15.73it/s]\u001b[A\n", " 90%|████████████████████████████████████▉ | 379/421 [00:23<00:02, 16.49it/s]\u001b[A\n", " 90%|█████████████████████████████████████ | 381/421 [00:23<00:02, 16.00it/s]\u001b[A\n", " 91%|█████████████████████████████████████▎ | 383/421 [00:24<00:02, 14.85it/s]\u001b[A\n", " 91%|█████████████████████████████████████▍ | 385/421 [00:24<00:02, 14.68it/s]\u001b[A\n", " 92%|█████████████████████████████████████▋ | 387/421 [00:24<00:02, 15.07it/s]\u001b[A\n", " 92%|█████████████████████████████████████▉ | 389/421 [00:24<00:02, 15.56it/s]\u001b[A\n", " 93%|██████████████████████████████████████ | 391/421 [00:24<00:01, 15.19it/s]\u001b[A\n", " 93%|██████████████████████████████████████▎ | 393/421 [00:24<00:01, 14.91it/s]\u001b[A\n", " 94%|██████████████████████████████████████▍ | 395/421 [00:24<00:01, 15.37it/s]\u001b[A\n", " 94%|██████████████████████████████████████▋ | 397/421 [00:24<00:01, 16.00it/s]\u001b[A\n", " 95%|██████████████████████████████████████▊ | 399/421 [00:25<00:01, 16.01it/s]\u001b[A\n", " 95%|███████████████████████████████████████ | 401/421 [00:25<00:01, 16.63it/s]\u001b[A\n", " 96%|███████████████████████████████████████▏ | 403/421 [00:25<00:01, 16.94it/s]\u001b[A\n", " 96%|███████████████████████████████████████▍ | 405/421 [00:25<00:00, 16.94it/s]\u001b[A\n", " 97%|███████████████████████████████████████▋ | 407/421 [00:25<00:00, 17.34it/s]\u001b[A\n", " 97%|███████████████████████████████████████▊ | 409/421 [00:25<00:00, 17.21it/s]\u001b[A\n", " 98%|████████████████████████████████████████ | 411/421 [00:25<00:00, 17.65it/s]\u001b[A\n", " 98%|████████████████████████████████████████▎| 414/421 [00:25<00:00, 17.90it/s]\u001b[A\n", " 99%|████████████████████████████████████████▌| 416/421 [00:26<00:00, 16.69it/s]\u001b[A\n", " 99%|████████████████████████████████████████▋| 418/421 [00:26<00:00, 16.98it/s]\u001b[A\n", " \u001b[A\n", " 78%|████████████████████████████▉ | 2500/3200 [1:41:23<27:53, 2.39s/it]\n", "100%|█████████████████████████████████████████| 421/421 [00:26<00:00, 17.07it/s]\u001b[A\n", " \u001b[ASaving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-2500\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-2500/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-2500/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-2500/preprocessor_config.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-1500] due to args.save_total_limit\n", " 94%|██████████████████████████████████▋ | 3000/3200 [2:01:43<08:04, 2.42s/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 = 421\n", " Batch size = 1\n", "\n", " 0%| | 0/421 [00:00<?, ?it/s]\u001b[A\n", " 0%|▏ | 2/421 [00:00<00:21, 19.56it/s]\u001b[A\n", " 1%|▍ | 4/421 [00:00<00:25, 16.52it/s]\u001b[A\n", " 1%|▌ | 6/421 [00:00<00:26, 15.87it/s]\u001b[A\n", " 2%|▊ | 8/421 [00:00<00:27, 14.95it/s]\u001b[A\n", " 2%|▉ | 10/421 [00:00<00:26, 15.41it/s]\u001b[A\n", " 3%|█▏ | 12/421 [00:00<00:25, 16.09it/s]\u001b[A\n", " 3%|█▍ | 14/421 [00:00<00:25, 15.98it/s]\u001b[A\n", " 4%|█▌ | 16/421 [00:00<00:24, 16.21it/s]\u001b[A\n", " 5%|█▉ | 19/421 [00:01<00:23, 17.36it/s]\u001b[A\n", " 5%|██ | 21/421 [00:01<00:22, 17.80it/s]\u001b[A\n", " 5%|██▎ | 23/421 [00:01<00:22, 17.68it/s]\u001b[A\n", " 6%|██▍ | 25/421 [00:01<00:22, 17.89it/s]\u001b[A\n", " 6%|██▋ | 27/421 [00:01<00:21, 17.97it/s]\u001b[A\n", " 7%|██▉ | 29/421 [00:01<00:21, 18.47it/s]\u001b[A\n", " 7%|███ | 31/421 [00:01<00:23, 16.89it/s]\u001b[A\n", " 8%|███▍ | 34/421 [00:02<00:23, 16.81it/s]\u001b[A\n", " 9%|███▌ | 36/421 [00:02<00:23, 16.61it/s]\u001b[A\n", " 9%|███▊ | 38/421 [00:02<00:23, 16.08it/s]\u001b[A\n", " 10%|███▉ | 40/421 [00:02<00:23, 16.07it/s]\u001b[A\n", " 10%|████▏ | 42/421 [00:02<00:23, 15.99it/s]\u001b[A\n", " 10%|████▍ | 44/421 [00:02<00:23, 16.02it/s]\u001b[A\n", " 11%|████▌ | 46/421 [00:02<00:24, 15.55it/s]\u001b[A\n", " 11%|████▊ | 48/421 [00:02<00:23, 15.84it/s]\u001b[A\n", " 12%|█████ | 51/421 [00:03<00:21, 17.56it/s]\u001b[A\n", " 13%|█████▎ | 53/421 [00:03<00:20, 18.07it/s]\u001b[A\n", " 13%|█████▍ | 55/421 [00:03<00:20, 17.56it/s]\u001b[A\n", " 14%|█████▋ | 57/421 [00:03<00:21, 16.90it/s]\u001b[A\n", " 14%|█████▉ | 60/421 [00:03<00:20, 17.81it/s]\u001b[A\n", " 15%|██████▏ | 62/421 [00:03<00:20, 17.75it/s]\u001b[A\n", " 15%|██████▍ | 64/421 [00:03<00:20, 17.73it/s]\u001b[A\n", " 16%|██████▌ | 66/421 [00:03<00:20, 17.44it/s]\u001b[A\n", " 16%|██████▊ | 68/421 [00:04<00:20, 17.06it/s]\u001b[A\n", " 17%|██████▉ | 70/421 [00:04<00:20, 17.47it/s]\u001b[A\n", " 17%|███████▏ | 72/421 [00:04<00:20, 17.40it/s]\u001b[A\n", " 18%|███████▍ | 74/421 [00:04<00:20, 17.20it/s]\u001b[A\n", " 18%|███████▋ | 77/421 [00:04<00:18, 18.12it/s]\u001b[A\n", " 19%|███████▉ | 79/421 [00:04<00:19, 17.24it/s]\u001b[A\n", " 19%|████████ | 81/421 [00:04<00:20, 16.91it/s]\u001b[A\n", " 20%|████████▎ | 83/421 [00:04<00:20, 16.88it/s]\u001b[A\n", " 20%|████████▍ | 85/421 [00:05<00:19, 17.43it/s]\u001b[A\n", " 21%|████████▋ | 87/421 [00:05<00:20, 16.51it/s]\u001b[A\n", " 21%|████████▉ | 89/421 [00:05<00:19, 16.99it/s]\u001b[A\n", " 22%|█████████ | 91/421 [00:05<00:19, 17.22it/s]\u001b[A\n", " 22%|█████████▎ | 93/421 [00:05<00:20, 16.00it/s]\u001b[A\n", " 23%|█████████▍ | 95/421 [00:05<00:19, 16.41it/s]\u001b[A\n", " 23%|█████████▋ | 97/421 [00:05<00:19, 16.60it/s]\u001b[A\n", " 24%|█████████▉ | 99/421 [00:05<00:20, 16.04it/s]\u001b[A\n", " 24%|█████████▊ | 101/421 [00:06<00:20, 15.69it/s]\u001b[A\n", " 24%|██████████ | 103/421 [00:06<00:19, 16.02it/s]\u001b[A\n", " 25%|██████████▏ | 105/421 [00:06<00:20, 15.50it/s]\u001b[A\n", " 25%|██████████▍ | 107/421 [00:06<00:19, 16.43it/s]\u001b[A\n", " 26%|██████████▌ | 109/421 [00:06<00:19, 16.28it/s]\u001b[A\n", " 26%|██████████▊ | 111/421 [00:06<00:19, 15.54it/s]\u001b[A\n", " 27%|███████████ | 113/421 [00:06<00:20, 14.69it/s]\u001b[A\n", " 27%|███████████▏ | 115/421 [00:06<00:21, 14.07it/s]\u001b[A\n", " 28%|███████████▍ | 117/421 [00:07<00:20, 15.07it/s]\u001b[A\n", " 28%|███████████▌ | 119/421 [00:07<00:19, 15.26it/s]\u001b[A\n", " 29%|███████████▊ | 121/421 [00:07<00:19, 15.51it/s]\u001b[A\n", " 29%|███████████▉ | 123/421 [00:07<00:19, 15.31it/s]\u001b[A\n", " 30%|████████████▏ | 125/421 [00:07<00:18, 15.80it/s]\u001b[A\n", " 30%|████████████▎ | 127/421 [00:07<00:19, 15.36it/s]\u001b[A\n", " 31%|████████████▌ | 129/421 [00:07<00:18, 16.21it/s]\u001b[A\n", " 31%|████████████▊ | 131/421 [00:07<00:18, 15.85it/s]\u001b[A\n", " 32%|████████████▉ | 133/421 [00:08<00:18, 15.50it/s]\u001b[A\n", " 32%|█████████████▏ | 135/421 [00:08<00:18, 15.82it/s]\u001b[A\n", " 33%|█████████████▎ | 137/421 [00:08<00:18, 15.19it/s]\u001b[A\n", " 33%|█████████████▌ | 139/421 [00:08<00:18, 15.64it/s]\u001b[A\n", " 33%|█████████████▋ | 141/421 [00:08<00:18, 15.50it/s]\u001b[A\n", " 34%|█████████████▉ | 143/421 [00:08<00:18, 15.27it/s]\u001b[A\n", " 34%|██████████████ | 145/421 [00:08<00:17, 15.92it/s]\u001b[A\n", " 35%|██████████████▎ | 147/421 [00:08<00:17, 15.69it/s]\u001b[A\n", " 35%|██████████████▌ | 149/421 [00:09<00:17, 15.41it/s]\u001b[A\n", " 36%|██████████████▋ | 151/421 [00:09<00:17, 15.19it/s]\u001b[A\n", " 36%|██████████████▉ | 153/421 [00:09<00:17, 15.60it/s]\u001b[A\n", " 37%|███████████████ | 155/421 [00:09<00:17, 14.86it/s]\u001b[A\n", " 37%|███████████████▎ | 157/421 [00:09<00:17, 15.04it/s]\u001b[A\n", " 38%|███████████████▍ | 159/421 [00:09<00:16, 15.76it/s]\u001b[A\n", " 38%|███████████████▋ | 161/421 [00:09<00:15, 16.34it/s]\u001b[A\n", " 39%|███████████████▊ | 163/421 [00:10<00:17, 14.90it/s]\u001b[A\n", " 39%|████████████████ | 165/421 [00:10<00:16, 15.27it/s]\u001b[A\n", " 40%|████████████████▎ | 167/421 [00:10<00:16, 15.56it/s]\u001b[A\n", " 40%|████████████████▍ | 169/421 [00:10<00:15, 15.94it/s]\u001b[A\n", " 41%|████████████████▋ | 171/421 [00:10<00:15, 16.10it/s]\u001b[A\n", " 41%|████████████████▊ | 173/421 [00:10<00:15, 16.10it/s]\u001b[A\n", " 42%|█████████████████ | 175/421 [00:10<00:15, 16.28it/s]\u001b[A\n", " 42%|█████████████████▏ | 177/421 [00:10<00:14, 16.60it/s]\u001b[A\n", " 43%|█████████████████▍ | 179/421 [00:11<00:15, 15.96it/s]\u001b[A\n", " 43%|█████████████████▋ | 181/421 [00:11<00:14, 16.21it/s]\u001b[A\n", " 44%|█████████████████▉ | 184/421 [00:11<00:13, 17.28it/s]\u001b[A\n", " 44%|██████████████████ | 186/421 [00:11<00:13, 17.24it/s]\u001b[A\n", " 45%|██████████████████▎ | 188/421 [00:11<00:13, 17.05it/s]\u001b[A\n", " 45%|██████████████████▌ | 190/421 [00:11<00:13, 16.77it/s]\u001b[A\n", " 46%|██████████████████▋ | 192/421 [00:11<00:14, 16.35it/s]\u001b[A\n", " 46%|██████████████████▉ | 194/421 [00:11<00:14, 16.21it/s]\u001b[A\n", " 47%|███████████████████ | 196/421 [00:11<00:13, 17.14it/s]\u001b[A\n", " 47%|███████████████████▎ | 198/421 [00:12<00:12, 17.46it/s]\u001b[A\n", " 48%|███████████████████▍ | 200/421 [00:12<00:13, 16.36it/s]\u001b[A\n", " 48%|███████████████████▋ | 202/421 [00:12<00:13, 16.39it/s]\u001b[A\n", " 48%|███████████████████▊ | 204/421 [00:12<00:13, 16.34it/s]\u001b[A\n", " 49%|████████████████████ | 206/421 [00:12<00:12, 16.70it/s]\u001b[A\n", " 49%|████████████████████▎ | 208/421 [00:12<00:13, 16.08it/s]\u001b[A\n", " 50%|████████████████████▍ | 210/421 [00:12<00:12, 16.49it/s]\u001b[A\n", " 50%|████████████████████▋ | 212/421 [00:12<00:12, 16.22it/s]\u001b[A\n", " 51%|████████████████████▊ | 214/421 [00:13<00:12, 16.30it/s]\u001b[A\n", " 52%|█████████████████████▏ | 217/421 [00:13<00:11, 17.52it/s]\u001b[A\n", " 52%|█████████████████████▎ | 219/421 [00:13<00:11, 16.95it/s]\u001b[A\n", " 52%|█████████████████████▌ | 221/421 [00:13<00:11, 16.68it/s]\u001b[A\n", " 53%|█████████████████████▋ | 223/421 [00:13<00:12, 16.10it/s]\u001b[A\n", " 53%|█████████████████████▉ | 225/421 [00:13<00:12, 16.32it/s]\u001b[A\n", " 54%|██████████████████████ | 227/421 [00:13<00:12, 15.99it/s]\u001b[A\n", " 54%|██████████████████████▎ | 229/421 [00:14<00:12, 15.93it/s]\u001b[A\n", " 55%|██████████████████████▍ | 231/421 [00:14<00:12, 15.52it/s]\u001b[A\n", " 55%|██████████████████████▋ | 233/421 [00:14<00:12, 14.70it/s]\u001b[A\n", " 56%|██████████████████████▉ | 235/421 [00:14<00:12, 14.88it/s]\u001b[A\n", " 56%|███████████████████████ | 237/421 [00:14<00:12, 15.22it/s]\u001b[A\n", " 57%|███████████████████████▎ | 239/421 [00:14<00:12, 14.94it/s]\u001b[A\n", " 57%|███████████████████████▍ | 241/421 [00:14<00:11, 15.30it/s]\u001b[A\n", " 58%|███████████████████████▋ | 243/421 [00:14<00:11, 16.18it/s]\u001b[A\n", " 58%|███████████████████████▊ | 245/421 [00:15<00:10, 16.29it/s]\u001b[A\n", " 59%|████████████████████████ | 247/421 [00:15<00:10, 16.50it/s]\u001b[A\n", " 59%|████████████████████████▏ | 249/421 [00:15<00:10, 16.64it/s]\u001b[A\n", " 60%|████████████████████████▍ | 251/421 [00:15<00:10, 16.26it/s]\u001b[A\n", " 60%|████████████████████████▋ | 253/421 [00:15<00:10, 16.11it/s]\u001b[A\n", " 61%|████████████████████████▊ | 255/421 [00:15<00:10, 15.58it/s]\u001b[A\n", " 61%|█████████████████████████▏ | 258/421 [00:15<00:09, 17.05it/s]\u001b[A\n", " 62%|█████████████████████████▎ | 260/421 [00:15<00:09, 16.69it/s]\u001b[A\n", " 62%|█████████████████████████▌ | 262/421 [00:16<00:10, 15.84it/s]\u001b[A\n", " 63%|█████████████████████████▋ | 264/421 [00:16<00:10, 15.30it/s]\u001b[A\n", " 63%|█████████████████████████▉ | 266/421 [00:16<00:10, 15.28it/s]\u001b[A\n", " 64%|██████████████████████████ | 268/421 [00:16<00:10, 14.91it/s]\u001b[A\n", " 64%|██████████████████████████▎ | 270/421 [00:16<00:09, 15.55it/s]\u001b[A\n", " 65%|██████████████████████████▍ | 272/421 [00:16<00:09, 15.11it/s]\u001b[A\n", " 65%|██████████████████████████▋ | 274/421 [00:16<00:10, 14.62it/s]\u001b[A\n", " 66%|██████████████████████████▉ | 276/421 [00:17<00:09, 15.38it/s]\u001b[A\n", " 66%|███████████████████████████ | 278/421 [00:17<00:09, 15.57it/s]\u001b[A\n", " 67%|███████████████████████████▎ | 280/421 [00:17<00:10, 14.09it/s]\u001b[A\n", " 67%|███████████████████████████▍ | 282/421 [00:17<00:10, 13.40it/s]\u001b[A\n", " 67%|███████████████████████████▋ | 284/421 [00:17<00:10, 12.70it/s]\u001b[A\n", " 68%|███████████████████████████▊ | 286/421 [00:17<00:10, 12.83it/s]\u001b[A\n", " 68%|████████████████████████████ | 288/421 [00:17<00:10, 13.27it/s]\u001b[A\n", " 69%|████████████████████████████▏ | 290/421 [00:18<00:09, 13.85it/s]\u001b[A\n", " 69%|████████████████████████████▍ | 292/421 [00:18<00:09, 13.28it/s]\u001b[A\n", " 70%|████████████████████████████▋ | 294/421 [00:18<00:09, 13.13it/s]\u001b[A\n", " 70%|████████████████████████████▊ | 296/421 [00:18<00:09, 13.11it/s]\u001b[A\n", " 71%|█████████████████████████████ | 298/421 [00:18<00:09, 13.35it/s]\u001b[A\n", " 71%|█████████████████████████████▏ | 300/421 [00:18<00:09, 13.03it/s]\u001b[A\n", " 72%|█████████████████████████████▍ | 302/421 [00:19<00:09, 13.16it/s]\u001b[A\n", " 72%|█████████████████████████████▌ | 304/421 [00:19<00:09, 12.90it/s]\u001b[A\n", " 73%|█████████████████████████████▊ | 306/421 [00:19<00:08, 12.93it/s]\u001b[A\n", " 73%|█████████████████████████████▉ | 308/421 [00:19<00:09, 12.47it/s]\u001b[A\n", " 74%|██████████████████████████████▏ | 310/421 [00:19<00:08, 13.37it/s]\u001b[A\n", " 74%|██████████████████████████████▍ | 312/421 [00:19<00:08, 13.57it/s]\u001b[A\n", " 75%|██████████████████████████████▌ | 314/421 [00:19<00:07, 14.14it/s]\u001b[A\n", " 75%|██████████████████████████████▊ | 316/421 [00:20<00:07, 14.25it/s]\u001b[A\n", " 76%|██████████████████████████████▉ | 318/421 [00:20<00:07, 14.59it/s]\u001b[A\n", " 76%|███████████████████████████████▏ | 320/421 [00:20<00:06, 15.01it/s]\u001b[A\n", " 76%|███████████████████████████████▎ | 322/421 [00:20<00:06, 15.34it/s]\u001b[A\n", " 77%|███████████████████████████████▌ | 324/421 [00:20<00:06, 15.88it/s]\u001b[A\n", " 77%|███████████████████████████████▋ | 326/421 [00:20<00:05, 16.27it/s]\u001b[A\n", " 78%|███████████████████████████████▉ | 328/421 [00:20<00:05, 15.98it/s]\u001b[A\n", " 78%|████████████████████████████████▏ | 330/421 [00:20<00:05, 16.75it/s]\u001b[A\n", " 79%|████████████████████████████████▎ | 332/421 [00:21<00:05, 16.69it/s]\u001b[A\n", " 79%|████████████████████████████████▌ | 334/421 [00:21<00:05, 16.58it/s]\u001b[A\n", " 80%|████████████████████████████████▋ | 336/421 [00:21<00:05, 16.72it/s]\u001b[A\n", " 80%|████████████████████████████████▉ | 338/421 [00:21<00:04, 17.40it/s]\u001b[A\n", " 81%|█████████████████████████████████ | 340/421 [00:21<00:04, 16.21it/s]\u001b[A\n", " 81%|█████████████████████████████████▎ | 342/421 [00:21<00:04, 16.81it/s]\u001b[A\n", " 82%|█████████████████████████████████▌ | 344/421 [00:21<00:04, 16.62it/s]\u001b[A\n", " 82%|█████████████████████████████████▋ | 346/421 [00:21<00:04, 16.67it/s]\u001b[A\n", " 83%|█████████████████████████████████▉ | 348/421 [00:21<00:04, 15.93it/s]\u001b[A\n", " 83%|██████████████████████████████████ | 350/421 [00:22<00:04, 15.81it/s]\u001b[A\n", " 84%|██████████████████████████████████▎ | 352/421 [00:22<00:04, 15.10it/s]\u001b[A\n", " 84%|██████████████████████████████████▍ | 354/421 [00:22<00:04, 14.31it/s]\u001b[A\n", " 85%|██████████████████████████████████▋ | 356/421 [00:22<00:04, 13.93it/s]\u001b[A\n", " 85%|██████████████████████████████████▊ | 358/421 [00:22<00:04, 13.15it/s]\u001b[A\n", " 86%|███████████████████████████████████ | 360/421 [00:22<00:04, 13.93it/s]\u001b[A\n", " 86%|███████████████████████████████████▎ | 362/421 [00:22<00:03, 14.77it/s]\u001b[A\n", " 86%|███████████████████████████████████▍ | 364/421 [00:23<00:03, 15.93it/s]\u001b[A\n", " 87%|███████████████████████████████████▋ | 366/421 [00:23<00:03, 15.90it/s]\u001b[A\n", " 87%|███████████████████████████████████▊ | 368/421 [00:23<00:03, 14.85it/s]\u001b[A\n", " 88%|████████████████████████████████████ | 370/421 [00:23<00:03, 15.88it/s]\u001b[A\n", " 88%|████████████████████████████████████▏ | 372/421 [00:23<00:03, 15.61it/s]\u001b[A\n", " 89%|████████████████████████████████████▍ | 374/421 [00:23<00:02, 16.22it/s]\u001b[A\n", " 89%|████████████████████████████████████▌ | 376/421 [00:23<00:02, 16.27it/s]\u001b[A\n", " 90%|████████████████████████████████████▊ | 378/421 [00:23<00:02, 15.98it/s]\u001b[A\n", " 90%|█████████████████████████████████████ | 380/421 [00:24<00:02, 14.62it/s]\u001b[A\n", " 91%|█████████████████████████████████████▏ | 382/421 [00:24<00:02, 14.08it/s]\u001b[A\n", " 91%|█████████████████████████████████████▍ | 384/421 [00:24<00:02, 13.71it/s]\u001b[A\n", " 92%|█████████████████████████████████████▌ | 386/421 [00:24<00:02, 14.31it/s]\u001b[A\n", " 92%|█████████████████████████████████████▊ | 388/421 [00:24<00:02, 14.64it/s]\u001b[A\n", " 93%|█████████████████████████████████████▉ | 390/421 [00:24<00:02, 15.44it/s]\u001b[A\n", " 93%|██████████████████████████████████████▏ | 392/421 [00:24<00:01, 14.68it/s]\u001b[A\n", " 94%|██████████████████████████████████████▎ | 394/421 [00:25<00:01, 15.21it/s]\u001b[A\n", " 94%|██████████████████████████████████████▌ | 396/421 [00:25<00:01, 16.18it/s]\u001b[A\n", " 95%|██████████████████████████████████████▊ | 398/421 [00:25<00:01, 15.84it/s]\u001b[A\n", " 95%|██████████████████████████████████████▉ | 400/421 [00:25<00:01, 16.20it/s]\u001b[A\n", " 95%|███████████████████████████████████████▏ | 402/421 [00:25<00:01, 16.26it/s]\u001b[A\n", " 96%|███████████████████████████████████████▎ | 404/421 [00:25<00:01, 16.56it/s]\u001b[A\n", " 96%|███████████████████████████████████████▌ | 406/421 [00:25<00:00, 17.37it/s]\u001b[A\n", " 97%|███████████████████████████████████████▋ | 408/421 [00:25<00:00, 17.06it/s]\u001b[A\n", " 97%|███████████████████████████████████████▉ | 410/421 [00:26<00:00, 17.41it/s]\u001b[A\n", " 98%|████████████████████████████████████████ | 412/421 [00:26<00:00, 18.07it/s]\u001b[A\n", " 98%|████████████████████████████████████████▎| 414/421 [00:26<00:00, 17.60it/s]\u001b[A\n", " 99%|████████████████████████████████████████▌| 416/421 [00:26<00:00, 16.38it/s]\u001b[A\n", " 99%|████████████████████████████████████████▋| 418/421 [00:26<00:00, 16.66it/s]\u001b[A\n", " \u001b[A\n", " 94%|██████████████████████████████████▋ | 3000/3200 [2:02:10<08:04, 2.42s/it]\n", "100%|█████████████████████████████████████████| 421/421 [00:26<00:00, 16.95it/s]\u001b[A\n", " \u001b[ASaving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-3000\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-3000/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-3000/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-3000/preprocessor_config.json\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "Deleting older checkpoint [wav2vec2-large-xls-r-300m-romansh-vallader/checkpoint-2000] due to args.save_total_limit\n", "100%|█████████████████████████████████████| 3200/3200 [2:11:10<00:00, 1.80s/it]\n", "\n", "Training completed. Do not forget to share your model on huggingface.co/models =)\n", "\n", "\n", "100%|█████████████████████████████████████| 3200/3200 [2:11:10<00:00, 2.46s/it]\n", "Saving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n", "***** Running Evaluation *****\n", " Num examples = 421\n", " Batch size = 1\n", "100%|█████████████████████████████████████████| 421/421 [00:26<00:00, 16.03it/s]\n", "Saving model checkpoint to ./wav2vec2-large-xls-r-300m-romansh-vallader\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/config.json\n", "Model weights saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/pytorch_model.bin\n", "Configuration saved in ./wav2vec2-large-xls-r-300m-romansh-vallader/preprocessor_config.json\n", "Upload file pytorch_model.bin: 98%|██████▉| 1.16G/1.18G [00:40<00:00, 32.1MB/s]To https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-vallader\n", " bacb858..1f1d53e main -> main\n", "\n", "Upload file pytorch_model.bin: 100%|███████| 1.18G/1.18G [00:41<00:00, 30.5MB/s]\n", "Dropping the following result as it does not have all the necessary fields:\n", "{'dataset': {'name': 'MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - RM-VALLADER', 'type': 'common_voice', 'args': 'Config: rm-vallader, Training split: train+validation, Eval split: test'}}\n", "To https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-vallader\n", " 1f1d53e..3e548a9 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=\"rm-vallader\" \\\n", "\t--output_dir=\"./wav2vec2-large-xls-r-300m-romansh-vallader\" \\\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=\"1\" \\\n", "\t--gradient_accumulation_steps=\"1\" \\\n", "\t--learning_rate=\"7e-5\" \\\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": null, "metadata": { "id": "0zBb4QMVcSeV" }, "outputs": [], "source": [ "# !rm -rf wav2vec2-large-xls-r-300m-bashkir" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "jxvhTTQ2cSeV" }, "outputs": [], "source": [ "!ls -ltr" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "okCO9-XTcSeV", "outputId": "a47bb25e-904a-4c1e-8871-d996a16b6bcc" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Filesystem Size Used Avail Use% Mounted on\n", "overlay 3.5T 1.2T 2.2T 34% /\n", "tmpfs 64M 0 64M 0% /dev\n", "tmpfs 87G 0 87G 0% /sys/fs/cgroup\n", "tmpfs 87G 0 87G 0% /dev/shm\n", "/dev/md0 3.5T 1.2T 2.2T 34% /etc/group\n", "tmpfs 87G 12K 87G 1% /proc/driver/nvidia\n", "/dev/vda1 49G 6.5G 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": null, "metadata": { "id": "axSDvjOMdkxW" }, "outputs": [], "source": [ "# !pip install -U datasets" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 238, "referenced_widgets": [ "7c34d36b28e54989b0c509eae1bd9a0f", "eba629a92467433c92840e4450e7a937", "cf1afb1025d24c1cbbb1eefd26535a26", "f347c0838adf462d886a4ae36a3a6b41", "37bdb17bf4734fd4b92759c874a4d4b8", "4685ef4f82764fada48035b4de9af9e2", "aab799184cf8453e9cf026a32abff619", "1795d07714684311b1ccea7514f298e4", "7fa8f65c508e4e629b1a2212aaa64ebc", "c139ed75ff4d47d593f8cb5f3fa4c105", "776dc15d8836456281084dc154d769e4", "f3a862eb1219484b8d9381fb0d16b063", "da3f94cc1140466cbcbdb3e03cbea8c2", "2fedf1edcc184d9b8c67712511f8bfef", "25142b9649ef403c8b37cdb7f9a8de4b", "8f5cd0e3111241b8a61914dac82acf73", "7340567ea42d42709f8099a249f6b5dd", "7365cf85ddff4b26a27c9b797c573949", "2fbc062ac19f4eb7a8adff2a5118bea4", "ae5b0f9f37e44e8e965f7e20dfdf3bfa", "24aeaf260d2240d08466c5e3a01d95cb", "06ec543be0a34943959c3140119c4d6e", "311cbd6bf6df4c35b7819e49fb55a562", "3bc2760daaa346b2b20d76d6cf4ed336", "c4b226675ad84ff29f62847767065469", "0be3f91b1071464d979c0c59baff32f4", "7c4a653d81474818b084b71657f71e0f", "cb10ec01c16a4c50bf8e4c8aec491aa2", "ec67f65de50b4038ac3b01496ef56f98", "4b2562825d8e4c5484008cd054e01216", "209d975f5d4e4300bf01bb6b2472d493", "690f71c3c232421c8cd92a28b5435b55", "4f4d422bdd49486c940713c19e754479", "e5d1a213afc04270926da41e12b30362", "30afb513746845b481227b3191df4c90", "c7017ddc94104c27b42658f27f275908", "155de8f44ddf4021a5d1d4d4968934db", "cb3b32862a12486f8625d667bb45c368", "832b4fcaf152402e84bfdaf9833d061f", "8af6a305cc8a4a038f74f39e6ea8f040", "4c316c3eddd64af1b4d892516e1ced03", "efd0fc9b3766457484533a6eb59f2cd4", "27d72d36fe604e5d96d6a979ed6d50ee", "f90669ec059249ca81a0e2c5891834db", "67d3fcb0869a4485b24846d3b1e34fca", "3db73d64f4e54cad8f8cd0f5facc33c0", "d434124da4654ada92573070353dbce1", "3c36f662c44e453ca935753e6dc18060", "0d0ab06d275d49f5b1ac57b28c53c158", "61771b0bdfe543b88fc8673a510a986c", "63d4b794d9df49c6ab6f77f10a76861d", "42bb543380e14d859f42e966b3c54bc2", "00a1878e3cda42e1982093e185935937", "9cce7704e9e74588aa7aa3b9ddf9672f", "a27c1dd0b5c447058bf8abde274d7085", "1ee70ac9891d4104ad801f75b4081c9f", "eda7343054624f4d8a2e2b981b4fab41", "f56579df97b94a5a8b3a0fbf32905687", "aee17658cd4b4fe49a759ad6c9d5a576", "3a6e34083c8f4066a6718c957958cfa6", "8148f4330d0f441998d9a3ca4942bc22", "9ea974dfe1184fe3897a7d9d031c7624", "a968de55d2e148f88084ac96444c17ee", "c0aeab2086de4ca7ad8b5f0bbcde009c", "05d04f345a3148dd9053a5d524592333", "7a68ba6f90a24162a973ba5146c2f546", "a4411af1dda24dec9b863793ccd22390", "f085643a56b94b74bb7e883598170f01", "ee8a677f68a147e5b10a35518616e264", "315ae5446f264660bbe6119e8261495d", "64b970adf3af40268fb60e38140157e2", "2ac4df7918404aed92611750471cd85f", "7bf164fec94c40858cf5280937f8e00a", "0e1672eeb5244df9bf0cbd095625d68a", "ee80362b77ef4375bb931af34bc16d07", "fed5fdea500f46618789c44aef2bff3b", "f49c5c9c58ee482a8264e422d4610a8a", "6a9e0e280ef7493eb4557429d6f53685", "c51fb67419ed47f98c5ed4ad4e33aeff", "2de6d3927c534397ab122a9cf6332a33", "f3891dcc62b74ccd8d5a61b0ca761b2a", "9958cd546fbe477092527a14bb3bfe21", "639f180d5e02425dba7d4c4bca07c59b", "4da0d9054bd74fb2a77bb40371c99a7b", "3f8a5e226fbf4175b4fa7f39a2a9d290", "41515b22976648aabe660b8df3506c4c", "b2a72b0caf104aee8dd95bff01cc52a4", "6b8769a26838449e9d7d45fc5cc7a6f6", "50862512d9c14dbd92f8cc3d795d4cd2", "352fc0a527024af8a284c53f4d521fec", "67653ac95966464994b1e0a889cfc5d9", "778d0a9a7de243eba8dd1c0caf3aa82e", "14eb779636914797867b7315f347839d", "25a5802292874e49bb42a1489ff54b31", "89a05d4149534d78935e169c6623f458", "49f46100f43346d2bdb402e2fd1a1951", "5e2e7ad6aa8f4f51adf7f6376b84f618", "2e918f153be0489dbf0ad64bc45c563c", "c319fa946f3e4380864aed6d3fbb77e7" ] }, "id": "82uZWUF_cSeW", "outputId": "e78215f2-d452-4d92-a94c-0a469f8760d4" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading and preparing dataset common_voice/rm-vallader to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/rm-vallader/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "005abadc03e34a32b8d6fa89096edcf2", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/114M [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0 examples [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0 examples [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0 examples [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0 examples [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "0 examples [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Dataset common_voice downloaded and prepared to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/rm-vallader/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b. Subsequent calls will reuse this data.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/rm-vallader/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "1010\n" ] } ], "source": [ "from datasets import load_dataset, load_metric, Audio\n", "\n", "common_voice_train = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"rm-vallader\", use_auth_token=True, split=\"train+validation\")\n", "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"rm-vallader\", use_auth_token=True, split=\"test\")\n", "\n", "print(len(common_voice_train))" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1Qa9wKa4cSeW", "outputId": "da721286-89ac-421c-a269-e779449488c6" }, "outputs": [ { "data": { "text/plain": [ "Dataset({\n", " features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment'],\n", " num_rows: 1010\n", "})" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "common_voice_train" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "H_KRIMbEcSeX", "outputId": "90601843-d465-4cd3-dff0-9d2302e02699" }, "outputs": [ { "data": { "text/plain": [ "3156.25" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(common_voice_train) * 100 / 32" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "ZUc_UAMbcSeX" }, "outputs": [], "source": [ "common_voice_train = common_voice_train.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])\n", "common_voice_test = common_voice_test.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "id": "OKxWKzjMcSeX" }, "outputs": [], "source": [ "from datasets import ClassLabel\n", "import random\n", "import pandas as pd\n", "from IPython.display import display, HTML\n", "\n", "def show_random_elements(dataset, num_examples=10):\n", " assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n", " picks = []\n", " for _ in range(num_examples):\n", " pick = random.randint(0, len(dataset)-1)\n", " while pick in picks:\n", " pick = random.randint(0, len(dataset)-1)\n", " picks.append(pick)\n", " \n", " df = pd.DataFrame(dataset[picks])\n", " display(HTML(df.to_html()))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 363 }, "id": "uR3e--0AcSeY", "outputId": "efb84606-2717-4040-ca02-86975a2f4824" }, "outputs": [ { "data": { "text/html": [ "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>sentence</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Meinsvart gronds sco pulits vadials.</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Tochen primavera sundel jeu eligius sco mistral e cheu dat ei nuot da marcadar.</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>El vegn a restar.</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>Meins aultas ein las frequenzas tier ils films dils carschi stadas.</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>Ses egls eran tut cotschens dil bargir.</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>La veta d’ina battaria cuoza entuorn quater onns.</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>La distribuziun fina el Grischun viva dalla glieud che va ellas apotecas dalla regiun.</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>Dalla vart dils umens eran las largias pli grondas.</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>Gia biars han empruau ei, mo negin ei puspei turnaus a casa.</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>Miu bab ha capiu da svegliar en mei l’amur per nies lungatg romontsch.</td>\n", " </tr>\n", " </tbody>\n", "</table>" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "show_random_elements(common_voice_train.remove_columns([\"path\", \"audio\"]), num_examples=10)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "id": "x_zfqqoVcSeY" }, "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": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "d8426e73abce4cbaa58a89aef1fce8b7", "ae51183c24fe42809d080fd15c298f92", "21c9c4302a76449784f314c15ca59bea", "fcc23e29fde64cde92f2ae57d7cabd78", "61ac7115c9b24ebb855343cc01b1d3f4", "90b3e47068e747c7be958d22fb56fe4f", "820d84c1afc7416e9368a246ab8d5ce9", "07447e6083b04bfeb04e5a601fe475bd", "822d95bb43c44a4394441d92e25120d7", "138580d9724141448ff8a5e11ef415ce", "1a03059af7bb40da924ecf3e709d7e0d", "b9d888877a7e4a24b07f4fb91ceda179", "36db5c636fcf46518685b91a168d9c11", "4407f3810d5d4820acf8db794ce305e6", "72fee1a44b5343a7add71c9649139317", "9b22b13729bf4f20b8b96da540cfaa3f", "90bde27c6e564ca285a65d6b594d6865", "256669df6862481cbd0bbcee229e2efe", "07b40214652e48adbae525787288795d", "57e054662b5d497b8e1f3d99fb72034f", "81a7889575ed4e0293f7ce56032e6edb", "00a619827a094be4ae891726e44ddd97" ] }, "id": "BQfNU564cSeZ", "outputId": "6ca3ff91-8acb-4096-d746-aed7edb4055a" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "bdb213ed6aab4c1b8e36f39f145f73e4", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2675 [00:00<?, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9118ed7bfda24b15878279a5dd8fea64", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1240 [00:00<?, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "common_voice_train = common_voice_train.map(remove_special_characters)\n", "common_voice_test = common_voice_test.map(remove_special_characters)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "id": "liHWiYx9cSeZ" }, "outputs": [], "source": [ "# start_with_ar = common_voice_train.filter(lambda example: \"⅛\" in example['sentence'])\n", "# start_with_ar[0]" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "id": "gdGzeDEVcSeZ" }, "outputs": [], "source": [ "# start_with_ar" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "id": "d9Fe6xH1cSea" }, "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", "# batch[\"sentence\"] = re.sub('&', 'and', batch[\"sentence\"])\n", " return batch" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "e106fee906b8408ebba822b4ff70693f", "af14186997de449f997936a81d69876b", "2d251c97292c4824a6cb218548c17353", "fcf8a57a02ec44398b95f4a64ad2f0fe", "8aaba2878c2c484e8fbf9d81354f924f", "95c3ba1f3cef4ca887dd8461db595c0a", "7092d73471c44875b496924bc82858df", "2d63896d07f64d91abb45c257ace72db", "781d2e3803574e2c841acfd1e090b84f", "d43443cf2579467a9cc3e9f05c607615", "19b70fdd00dc47f8b79f0d3acc68d11a", "992b23b615fb4e88a92782c64ad60cc2", "46031a26e4ff42819f1169eb07718b46", "0c8b1327b27449a49f9b71fdc80d831c", "c22392fb7cf0489caf741568e796fc9d", "b17ceb2a58d64747aafd29836e681e02", "cb8b0320a4794b278f86c33bbfc9825f", "1e7f593023d544e1afe46359567abfca", "33fffaf4bc4a405187a2dd4eaa7ffc67", "173c6246acdb4a3bbf6dce2e236499a2", "478464758f2b455bb8848ef4046ed11d", "ce845667dcf54353b02299f85dcda29d" ] }, "id": "f8K35VABcSea", "outputId": "3c0f55b5-3d44-4058-b362-896ebb58901c" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "46bf3dc04b214ebebfa87e0df4dfbfbe", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/2675 [00:00<?, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a7d33c176a3c4988b3aa1b53086bdfab", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1240 [00:00<?, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "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": 15, "metadata": { "id": "DOIBoakvcSea" }, "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": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 81, "referenced_widgets": [ "43a3718f19944ea7bda27a96e3816a78", "2ec6b96f3d8449c08a8b62b85ccb57dc", "8137d055bfd14a058a8755d00e5fe260", "6fa1c2f06d0c43c38c76a7ace7c178a5", "d8593055a0ea45f5ab13377c18e2b1e0", "85ff02f4cd7141a4aba5e1e83bb144d2", "fe412730e037441b961a664573d02ae7", "a33fe3bf150949fd9679ff1fe91d4433", "49aa86ddf29944b281b830b99e1ac4fe", "efb5e6e4970f43d1b6197e4aaedac0b7", "6e1517cd2bed4a35b52de6cdc812b75c", "557ddd52295c43a69b6fd2689edb46b4", "19630b62bebe4a8f9e775e59ee46fb9c", "4256584d0f934678901c4c1ac7f73d42", "0120e6cb1edc429ebf0a6437dc3378fe", "d9c616f1d67c4590a55bf797d8ab1904", "2d96a892d0a94a89b756e23ff19a1c1f", "c87e36307bf84cf4970afce9e496117d", "20d3b7a6a43143419d9cb64e557b3acc", "16dd9300014545caa901274f385e6a91", "c6c51e30cbb1472f9e1a49bc0f5bb2cc", "002decc6fb504205ae9f61a4871e1532" ] }, "id": "ZvFltuhucSea", "outputId": "fb969f7f-7172-4d82-8116-3dab25bd85a2" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2f09ddfb67134b2eb340ef55354838b0", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1 [00:00<?, ?ba/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5b052409ca654eaebf73297ea9026cdc", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/1 [00:00<?, ?ba/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "vocab_train = common_voice_train.map(extract_all_chars, batched=True, batch_size=-1, keep_in_memory=True, remove_columns=common_voice_train.column_names)\n", "vocab_test = common_voice_test.map(extract_all_chars, batched=True, batch_size=-1, keep_in_memory=True, remove_columns=common_voice_test.column_names)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "id": "FJD7IXLkcSeb" }, "outputs": [], "source": [ "vocab_list = list(set(vocab_train[\"vocab\"][0]) | set(vocab_test[\"vocab\"][0]))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "e50XUYe3cSeb", "outputId": "769619ae-7ad5-4504-f454-34a24d642534" }, "outputs": [ { "data": { "text/plain": [ "{' ': 0,\n", " 'a': 1,\n", " 'b': 2,\n", " 'c': 3,\n", " 'd': 4,\n", " 'e': 5,\n", " 'f': 6,\n", " 'g': 7,\n", " 'h': 8,\n", " 'i': 9,\n", " 'j': 10,\n", " 'k': 11,\n", " 'l': 12,\n", " 'm': 13,\n", " 'n': 14,\n", " 'o': 15,\n", " 'p': 16,\n", " 'q': 17,\n", " 'r': 18,\n", " 's': 19,\n", " 't': 20,\n", " 'u': 21,\n", " 'v': 22,\n", " 'w': 23,\n", " 'x': 24,\n", " 'y': 25,\n", " 'z': 26,\n", " '«': 27,\n", " '»': 28,\n", " 'à': 29,\n", " 'ä': 30,\n", " 'è': 31,\n", " 'é': 32,\n", " 'ò': 33,\n", " 'ö': 34,\n", " 'ü': 35}" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vocab_dict = {v: k for k, v in enumerate(sorted(vocab_list))}\n", "vocab_dict" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 128 }, "id": "wWofPlfMcSeb", "outputId": "cf9d5cdb-ffe1-46d5-af5c-f7c34cb4b59d" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "38\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "file ./config.json not found\n", "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py:1001: FutureWarning: `create_repo` now takes `token` as an optional positional argument. Be sure to adapt your code!\n", " warnings.warn(\n", "Cloning https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-sursilvan into local empty directory.\n", "To https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-sursilvan\n", " 00e5ead..0c47ae0 main -> main\n", "\n" ] }, { "data": { "text/plain": [ "'https://huggingface.co/infinitejoy/wav2vec2-large-xls-r-300m-romansh-sursilvan/commit/0c47ae07e50d16537a12a7574e6e2f077d11cd3d'" ] }, "execution_count": 19, "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-romansh-sursilvan\"\n", "\n", "# tokenizer.save_pretrained(repo_name)\n", "\n", "tokenizer.push_to_hub(repo_name)" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1XVJcIykcSeb", "outputId": "67c53812-24ce-4dee-bb95-608971d61338" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2022-01-30 07:10:29-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/research_projects/robust-speech-event/eval.py\n", "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 4738 (4.6K) [text/plain]\n", "Saving to: ‘eval.py’\n", "\n", "eval.py 100%[===================>] 4.63K --.-KB/s in 0s \n", "\n", "2022-01-30 07:10:29 (16.6 MB/s) - ‘eval.py’ saved [4738/4738]\n", "\n", "total 1232584\n", "-rw-r--r-- 1 ovh ovh 300 Jan 30 02:51 vocab.json\n", "-rw-r--r-- 1 ovh ovh 260 Jan 30 02:51 tokenizer_config.json\n", "-rw-r--r-- 1 ovh ovh 309 Jan 30 02:51 special_tokens_map.json\n", "-rw-r--r-- 1 ovh ovh 23 Jan 30 02:51 added_tokens.json\n", "drwxr-xr-x 2 ovh ovh 4096 Jan 30 04:36 checkpoint-500\n", "drwxr-xr-x 2 ovh ovh 4096 Jan 30 06:22 checkpoint-1000\n", "-rw-r--r-- 1 ovh ovh 2521 Jan 30 07:06 trainer_state.json\n", "-rw-r--r-- 1 ovh ovh 197 Jan 30 07:06 train_results.json\n", "-rw-r--r-- 1 ovh ovh 224 Jan 30 07:06 eval_results.json\n", "-rw-r--r-- 1 ovh ovh 2033 Jan 30 07:06 config.json\n", "-rw-r--r-- 1 ovh ovh 398 Jan 30 07:06 all_results.json\n", "-rw-r--r-- 1 ovh ovh 1262063089 Jan 30 07:06 pytorch_model.bin\n", "-rw-r--r-- 1 ovh ovh 212 Jan 30 07:06 preprocessor_config.json\n", "-rw-r--r-- 1 ovh ovh 3055 Jan 30 07:06 training_args.bin\n", "-rw-r--r-- 1 ovh ovh 1709 Jan 30 07:08 README.md\n", "-rw-r--r-- 1 ovh ovh 4738 Jan 30 07:10 eval.py\n", "-rw-r--r-- 1 ovh ovh 30348 Jan 30 07:10 run_speech_recognition_ctc.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-irish\n", "!cp run_speech_recognition_ctc.py wav2vec2-large-xls-r-300m-irish\n", "!ls -ltr wav2vec2-large-xls-r-300m-irish" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "id": "OLB-MXricSec", "outputId": "784016e5-2c0a-4235-b432-96bf126b33ba" }, "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-i;python eval.py \\\n", " --model_id ./ --dataset mozilla-foundation/common_voice_7_0 --config kmr --split test --log_outputs" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "id": "aoMHnv5ocSec" }, "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-irish; python eval.py \\\n", " --model_id ./ --dataset speech-recognition-community-v2/dev_data \\\n", " --config kmr --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": "5vvo9g7HcSec", "outputId": "c2cab8b0-2b67-4039-b8ca-9ab13c9629c3" }, "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<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f9bf2ab0d2fa4d3f9235cc6d1ab772f1", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/574 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "b0791474a34043da8057e06741472ade", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/23.0 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "1ccbd582d616458b87c76ac8dc5b6b36", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/309 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# from transformers import AutoModelForCTC, Wav2Vec2Processor\n", "\n", "# model = AutoModelForCTC.from_pretrained(\"infinitejoy/wav2vec2-large-xls-r-300m-bashkir\")\n", "# processor = Wav2Vec2Processor.from_pretrained(\"infinitejoy/wav2vec2-large-xls-r-300m-bashkir\")\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "referenced_widgets": [ "013fabff2ea243a0a728a79b8f54ae09", "a8d9ca6d024f46f58301bfbcc475e41a", "b336e2647c05466d87a11dfa326e30d6", "8e6962320ad944439261482617be4869", "99de2ef750aa49fd986965d66853a5ea", "765670f93e5f4c2e849c98d53e616f38", "812abafc8f6b49e3a498718d034a379b" ] }, "id": "9yVf94nEcSec", "outputId": "60fbb3b8-692c-4418-c222-c734e48c4db1" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "013fabff2ea243a0a728a79b8f54ae09", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/1.99k [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a8d9ca6d024f46f58301bfbcc475e41a", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/1.18G [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "b336e2647c05466d87a11dfa326e30d6", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/212 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8e6962320ad944439261482617be4869", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/260 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "99de2ef750aa49fd986965d66853a5ea", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/520 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "765670f93e5f4c2e849c98d53e616f38", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/23.0 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "812abafc8f6b49e3a498718d034a379b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/309 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "ename": "AssertionError", "evalue": "55", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-23-c6863db4730f>\u001b[0m in \u001b[0;36m<module>\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": 1, "metadata": { "colab": { "referenced_widgets": [ "42ac3a57a96b4987b0c62aa41aa13702", "29dbfe94c1e9436ea3feefd9a7ba5d34", "acd0b1dccad24943bf760273d89aced3" ] }, "id": "z26_Ce-kcSed", "outputId": "fb46fc7b-5450-4d76-e2cb-3b6417133d44" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/lv/7.0.0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "81d295b921134614b692ce51d86e1fda", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/1.99k [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d618ab22d4eb4d34b2b1617e90b5aa65", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/212 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8662d18dadf14176b7fa000759f024bd", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/1.18G [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c7fa500c0af44fa5a606d356e44821a7", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/293 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d56ae9108d3d423fa9a346f224cc9a4a", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/342 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "e46d33d2cbd24556936476c45c4303d9", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/23.0 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4b32d601a20941129c3ab246c3d817ca", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Downloading: 0%| | 0.00/502 [00:00<?, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2bae0dc8d53349cf94dee689641a192c", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/10 [00:00<?, ?ex/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "['nebija nekā tīra ko uzvilkt', 'cēlonis tam ne viens vien', 'visi vilki nav pelēki', 'iedzert aukstu alu būtu labi', 'vai mani mati bija glīti', 'lēnām nesasteidz', 'nerunā man rupjības', 'es vairs nevaru būt tavs elks', 'es atradu mūsu zemes gabalu', 'ko tas sīkais sūds ar mani darītu']\n", "['Nebija nekā tīra, ko uzvilkt?', 'Cēlonis tam - ne viens vien.', 'Visi vilki nav pelēki.', 'Iedzert aukstu alu būtu labi.', 'Vai mani mati bija glīti?', 'Lēnām, nesasteidz.', 'Nerunā man rupjības.', 'Es vairs nevaru būt tavs elks.', 'Es atradu mūsu zemes gabalu.', 'Ko tas sīkais sūds ar mani darītu?']\n" ] } ], "source": [ "from datasets import Audio, Dataset, load_dataset, load_metric\n", "from transformers import AutoFeatureExtractor, pipeline\n", "\n", "dataset = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"lv\", use_auth_token=True, split=\"train+validation\")\n", "\n", "# for testing: only process the first two examples as a test\n", "dataset = dataset.select(range(10))\n", "\n", "repo_name = 'infinitejoy/wav2vec2-large-xls-r-300m-latvian'\n", "\n", "# load processor\n", "feature_extractor = AutoFeatureExtractor.from_pretrained(repo_name)\n", "# feature_extractor = processor_with_lm.feature_extractor\n", "sampling_rate = feature_extractor.sampling_rate\n", "\n", "# resample audio\n", "dataset = dataset.cast_column(\"audio\", Audio(sampling_rate=sampling_rate))\n", "\n", "# load eval pipeline\n", "asr = pipeline(\"automatic-speech-recognition\", model=repo_name, feature_extractor=feature_extractor)\n", "\n", "# map function to decode audio\n", "def map_to_pred(batch):\n", " prediction = asr(\n", " batch[\"audio\"][\"array\"])\n", "\n", " batch[\"prediction\"] = prediction[\"text\"]\n", " batch[\"target\"] = batch[\"sentence\"]\n", " return batch\n", "\n", "# run inference on all examples\n", "result = dataset.map(map_to_pred, remove_columns=dataset.column_names)\n", "print(result[\"prediction\"])\n", "\n", "print(result['target'])" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "W0ajacuBcSed" }, "outputs": [ { "data": { "text/plain": [ "\"e'ess' qted j'ms' ' ɓ'jhm s' s'm' jtj' jtr'm 'v' ɓ'x'\"" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result[0][\"prediction\"].replace('[UNK]', '')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "accelerator": "GPU", "colab": { "name": "hausa_training_script.ipynb", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "002decc6fb504205ae9f61a4871e1532": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "00a1878e3cda42e1982093e185935937": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "00a619827a094be4ae891726e44ddd97": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "0120e6cb1edc429ebf0a6437dc3378fe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_16dd9300014545caa901274f385e6a91", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_20d3b7a6a43143419d9cb64e557b3acc", "value": 1 } }, "05d04f345a3148dd9053a5d524592333": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "06ec543be0a34943959c3140119c4d6e": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "07447e6083b04bfeb04e5a601fe475bd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "07b40214652e48adbae525787288795d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "0b83a8775ea1441980d8ba945be752fe": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "0be3f91b1071464d979c0c59baff32f4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_209d975f5d4e4300bf01bb6b2472d493", "max": 49716, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_4b2562825d8e4c5484008cd054e01216", "value": 49716 } }, "0c8b1327b27449a49f9b71fdc80d831c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1e7f593023d544e1afe46359567abfca", "placeholder": "", "style": "IPY_MODEL_cb8b0320a4794b278f86c33bbfc9825f", "value": "" } }, "0d0ab06d275d49f5b1ac57b28c53c158": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a27c1dd0b5c447058bf8abde274d7085", "placeholder": "", "style": "IPY_MODEL_9cce7704e9e74588aa7aa3b9ddf9672f", "value": " 1324/0 [00:01<00:00, 1353.56 examples/s]" } }, "0e1672eeb5244df9bf0cbd095625d68a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "0f6b3cf1d33f46f594934874170bcd83": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "127389ec566e423ab9a8f60a9d61caaa": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "TextModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "TextModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "TextView", "continuous_update": true, "description": "Username:", "description_tooltip": null, "disabled": false, "layout": "IPY_MODEL_e549178ba75f4939aba6ae1cf743722a", "placeholder": "", "style": "IPY_MODEL_0f6b3cf1d33f46f594934874170bcd83", "value": "infinitejoy" } }, "138580d9724141448ff8a5e11ef415ce": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "14eb779636914797867b7315f347839d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c319fa946f3e4380864aed6d3fbb77e7", "placeholder": "", "style": "IPY_MODEL_2e918f153be0489dbf0ad64bc45c563c", "value": " 30/0 [00:00<00:00, 131.50 examples/s]" } }, "155de8f44ddf4021a5d1d4d4968934db": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_efd0fc9b3766457484533a6eb59f2cd4", "max": 63636525, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_4c316c3eddd64af1b4d892516e1ced03", "value": 63636525 } }, "16dd9300014545caa901274f385e6a91": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "173c6246acdb4a3bbf6dce2e236499a2": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "1795d07714684311b1ccea7514f298e4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "19630b62bebe4a8f9e775e59ee46fb9c": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "19b70fdd00dc47f8b79f0d3acc68d11a": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1a03059af7bb40da924ecf3e709d7e0d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1e7f593023d544e1afe46359567abfca": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1ee70ac9891d4104ad801f75b4081c9f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_f56579df97b94a5a8b3a0fbf32905687", "IPY_MODEL_aee17658cd4b4fe49a759ad6c9d5a576", "IPY_MODEL_3a6e34083c8f4066a6718c957958cfa6" ], "layout": "IPY_MODEL_eda7343054624f4d8a2e2b981b4fab41" } }, "209d975f5d4e4300bf01bb6b2472d493": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "20d3b7a6a43143419d9cb64e557b3acc": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "21c9c4302a76449784f314c15ca59bea": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_820d84c1afc7416e9368a246ab8d5ce9", "placeholder": "", "style": "IPY_MODEL_90b3e47068e747c7be958d22fb56fe4f", "value": "" } }, "24aeaf260d2240d08466c5e3a01d95cb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "25142b9649ef403c8b37cdb7f9a8de4b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ae5b0f9f37e44e8e965f7e20dfdf3bfa", "max": 2984, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_2fbc062ac19f4eb7a8adff2a5118bea4", "value": 2984 } }, "256669df6862481cbd0bbcee229e2efe": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "25a5802292874e49bb42a1489ff54b31": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "27d72d36fe604e5d96d6a979ed6d50ee": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "2ac4df7918404aed92611750471cd85f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "2d251c97292c4824a6cb218548c17353": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7092d73471c44875b496924bc82858df", "placeholder": "", "style": "IPY_MODEL_95c3ba1f3cef4ca887dd8461db595c0a", "value": "" } }, "2d63896d07f64d91abb45c257ace72db": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "2d96a892d0a94a89b756e23ff19a1c1f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "2de6d3927c534397ab122a9cf6332a33": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4da0d9054bd74fb2a77bb40371c99a7b", "placeholder": "", "style": "IPY_MODEL_639f180d5e02425dba7d4c4bca07c59b", "value": "" } }, "2e918f153be0489dbf0ad64bc45c563c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "2ec6b96f3d8449c08a8b62b85ccb57dc": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "2fbc062ac19f4eb7a8adff2a5118bea4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "2fedf1edcc184d9b8c67712511f8bfef": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7365cf85ddff4b26a27c9b797c573949", "placeholder": "", "style": "IPY_MODEL_7340567ea42d42709f8099a249f6b5dd", "value": "Downloading: 100%" } }, "30afb513746845b481227b3191df4c90": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "311cbd6bf6df4c35b7819e49fb55a562": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_c4b226675ad84ff29f62847767065469", "IPY_MODEL_0be3f91b1071464d979c0c59baff32f4", "IPY_MODEL_7c4a653d81474818b084b71657f71e0f" ], "layout": "IPY_MODEL_3bc2760daaa346b2b20d76d6cf4ed336" } }, "315ae5446f264660bbe6119e8261495d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "info", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ee80362b77ef4375bb931af34bc16d07", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_0e1672eeb5244df9bf0cbd095625d68a", "value": 0 } }, "32eb83bb6fd34c56bb345368e47e8f6f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aa47a09bf444413ba95322d979c1908c", "placeholder": "", "style": "IPY_MODEL_ce8bb7d0fb744e7b9ce2ff35cfdbc679", "value": "<center>\n<img src=https://huggingface.co/front/assets/huggingface_logo-noborder.svg alt='Hugging Face'>\n<br>\n<b>The AI community building the future</b>\n<br>\nImmediately click login after typing your password or it might be stored in plain text in this notebook file.\n</center>" } }, "33fffaf4bc4a405187a2dd4eaa7ffc67": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "34417f648cd54ed5b6d91f53af3e2713": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_127389ec566e423ab9a8f60a9d61caaa", "IPY_MODEL_4e4bc5550505497ba35f6bd7dde2893f" ], "layout": "IPY_MODEL_0b83a8775ea1441980d8ba945be752fe" } }, "352fc0a527024af8a284c53f4d521fec": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "36db5c636fcf46518685b91a168d9c11": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "37bdb17bf4734fd4b92759c874a4d4b8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_776dc15d8836456281084dc154d769e4", "placeholder": "", "style": "IPY_MODEL_c139ed75ff4d47d593f8cb5f3fa4c105", "value": " 9.88k/9.88k [00:00<00:00, 9.35kB/s]" } }, "3a6e34083c8f4066a6718c957958cfa6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7a68ba6f90a24162a973ba5146c2f546", "placeholder": "", "style": "IPY_MODEL_05d04f345a3148dd9053a5d524592333", "value": " 134/0 [00:00<00:00, 369.59 examples/s]" } }, "3bc2760daaa346b2b20d76d6cf4ed336": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3c36f662c44e453ca935753e6dc18060": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "info", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_00a1878e3cda42e1982093e185935937", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_42bb543380e14d859f42e966b3c54bc2", "value": 1 } }, "3db73d64f4e54cad8f8cd0f5facc33c0": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3f8a5e226fbf4175b4fa7f39a2a9d290": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "41515b22976648aabe660b8df3506c4c": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "4256584d0f934678901c4c1ac7f73d42": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c87e36307bf84cf4970afce9e496117d", "placeholder": "", "style": "IPY_MODEL_2d96a892d0a94a89b756e23ff19a1c1f", "value": "100%" } }, "42bb543380e14d859f42e966b3c54bc2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "43a3718f19944ea7bda27a96e3816a78": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_8137d055bfd14a058a8755d00e5fe260", "IPY_MODEL_6fa1c2f06d0c43c38c76a7ace7c178a5", "IPY_MODEL_d8593055a0ea45f5ab13377c18e2b1e0" ], "layout": "IPY_MODEL_2ec6b96f3d8449c08a8b62b85ccb57dc" } }, "4407f3810d5d4820acf8db794ce305e6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_256669df6862481cbd0bbcee229e2efe", "placeholder": "", "style": "IPY_MODEL_90bde27c6e564ca285a65d6b594d6865", "value": "" } }, "46031a26e4ff42819f1169eb07718b46": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4685ef4f82764fada48035b4de9af9e2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "478464758f2b455bb8848ef4046ed11d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "49aa86ddf29944b281b830b99e1ac4fe": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "49f46100f43346d2bdb402e2fd1a1951": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "4b2562825d8e4c5484008cd054e01216": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "4c316c3eddd64af1b4d892516e1ced03": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "4da0d9054bd74fb2a77bb40371c99a7b": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4e4bc5550505497ba35f6bd7dde2893f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "PasswordModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "PasswordModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "PasswordView", "continuous_update": true, "description": "Password:", "description_tooltip": null, "disabled": false, "layout": "IPY_MODEL_7d3231a0b7794b11af662170b352d9e0", "placeholder": "", "style": "IPY_MODEL_9c28978adf974326a21259ae56f47fe9", "value": "" } }, "4f4d422bdd49486c940713c19e754479": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "50862512d9c14dbd92f8cc3d795d4cd2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_67653ac95966464994b1e0a889cfc5d9", "IPY_MODEL_778d0a9a7de243eba8dd1c0caf3aa82e", "IPY_MODEL_14eb779636914797867b7315f347839d" ], "layout": "IPY_MODEL_352fc0a527024af8a284c53f4d521fec" } }, "50a1252082d942b09bfc620a9fa9d1d0": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "VBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "VBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "VBoxView", "box_style": "", "children": [ "IPY_MODEL_32eb83bb6fd34c56bb345368e47e8f6f", "IPY_MODEL_34417f648cd54ed5b6d91f53af3e2713", "IPY_MODEL_7518572223ac480b89af2ab71f38b2ed" ], "layout": "IPY_MODEL_e270b7c82f784ebbbba4b17fb07c310d" } }, "557ddd52295c43a69b6fd2689edb46b4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_4256584d0f934678901c4c1ac7f73d42", "IPY_MODEL_0120e6cb1edc429ebf0a6437dc3378fe", "IPY_MODEL_d9c616f1d67c4590a55bf797d8ab1904" ], "layout": "IPY_MODEL_19630b62bebe4a8f9e775e59ee46fb9c" } }, "57e054662b5d497b8e1f3d99fb72034f": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "5e2e7ad6aa8f4f51adf7f6376b84f618": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "61771b0bdfe543b88fc8673a510a986c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "61ac7115c9b24ebb855343cc01b1d3f4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1a03059af7bb40da924ecf3e709d7e0d", "placeholder": "", "style": "IPY_MODEL_138580d9724141448ff8a5e11ef415ce", "value": " 1386/? [00:00<00:00, 3063.39ex/s]" } }, "639f180d5e02425dba7d4c4bca07c59b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "63d4b794d9df49c6ab6f77f10a76861d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "64b970adf3af40268fb60e38140157e2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f49c5c9c58ee482a8264e422d4610a8a", "placeholder": "", "style": "IPY_MODEL_fed5fdea500f46618789c44aef2bff3b", "value": " 0/0 [00:00<?, ? examples/s]" } }, "67653ac95966464994b1e0a889cfc5d9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_89a05d4149534d78935e169c6623f458", "placeholder": "", "style": "IPY_MODEL_25a5802292874e49bb42a1489ff54b31", "value": "" } }, "67d3fcb0869a4485b24846d3b1e34fca": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_d434124da4654ada92573070353dbce1", "IPY_MODEL_3c36f662c44e453ca935753e6dc18060", "IPY_MODEL_0d0ab06d275d49f5b1ac57b28c53c158" ], "layout": "IPY_MODEL_3db73d64f4e54cad8f8cd0f5facc33c0" } }, "690f71c3c232421c8cd92a28b5435b55": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "6a9e0e280ef7493eb4557429d6f53685": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_2de6d3927c534397ab122a9cf6332a33", "IPY_MODEL_f3891dcc62b74ccd8d5a61b0ca761b2a", "IPY_MODEL_9958cd546fbe477092527a14bb3bfe21" ], "layout": "IPY_MODEL_c51fb67419ed47f98c5ed4ad4e33aeff" } }, "6b8769a26838449e9d7d45fc5cc7a6f6": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "6e1517cd2bed4a35b52de6cdc812b75c": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "6fa1c2f06d0c43c38c76a7ace7c178a5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_49aa86ddf29944b281b830b99e1ac4fe", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_a33fe3bf150949fd9679ff1fe91d4433", "value": 1 } }, "7092d73471c44875b496924bc82858df": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "72fee1a44b5343a7add71c9649139317": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_57e054662b5d497b8e1f3d99fb72034f", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_07b40214652e48adbae525787288795d", "value": 1 } }, "7340567ea42d42709f8099a249f6b5dd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "7365cf85ddff4b26a27c9b797c573949": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7518572223ac480b89af2ab71f38b2ed": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ButtonModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ButtonView", "button_style": "", "description": "Login", "disabled": false, "icon": "", "layout": "IPY_MODEL_e410e7aecf23433f880a0f7169a8ce97", "style": "IPY_MODEL_e5124c5171e04625b70795e4b7a18819", "tooltip": "" } }, "776dc15d8836456281084dc154d769e4": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "778d0a9a7de243eba8dd1c0caf3aa82e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "info", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5e2e7ad6aa8f4f51adf7f6376b84f618", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_49f46100f43346d2bdb402e2fd1a1951", "value": 1 } }, "781d2e3803574e2c841acfd1e090b84f": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "7a68ba6f90a24162a973ba5146c2f546": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7bf164fec94c40858cf5280937f8e00a": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7c34d36b28e54989b0c509eae1bd9a0f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_cf1afb1025d24c1cbbb1eefd26535a26", "IPY_MODEL_f347c0838adf462d886a4ae36a3a6b41", "IPY_MODEL_37bdb17bf4734fd4b92759c874a4d4b8" ], "layout": "IPY_MODEL_eba629a92467433c92840e4450e7a937" } }, "7c4a653d81474818b084b71657f71e0f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_4f4d422bdd49486c940713c19e754479", "placeholder": "", "style": "IPY_MODEL_690f71c3c232421c8cd92a28b5435b55", "value": " 49.7k/49.7k [00:00<00:00, 5.02kB/s]" } }, "7d3231a0b7794b11af662170b352d9e0": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7fa8f65c508e4e629b1a2212aaa64ebc": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8137d055bfd14a058a8755d00e5fe260": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_fe412730e037441b961a664573d02ae7", "placeholder": "", "style": "IPY_MODEL_85ff02f4cd7141a4aba5e1e83bb144d2", "value": "100%" } }, "8148f4330d0f441998d9a3ca4942bc22": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "81a7889575ed4e0293f7ce56032e6edb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "820d84c1afc7416e9368a246ab8d5ce9": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "822d95bb43c44a4394441d92e25120d7": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "832b4fcaf152402e84bfdaf9833d061f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "85ff02f4cd7141a4aba5e1e83bb144d2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "89a05d4149534d78935e169c6623f458": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8aaba2878c2c484e8fbf9d81354f924f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_19b70fdd00dc47f8b79f0d3acc68d11a", "placeholder": "", "style": "IPY_MODEL_d43443cf2579467a9cc3e9f05c607615", "value": " 1386/? [00:00<00:00, 3192.10ex/s]" } }, "8af6a305cc8a4a038f74f39e6ea8f040": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8f5cd0e3111241b8a61914dac82acf73": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_06ec543be0a34943959c3140119c4d6e", "placeholder": "", "style": "IPY_MODEL_24aeaf260d2240d08466c5e3a01d95cb", "value": " 2.98k/2.98k [00:00<00:00, 6.54kB/s]" } }, "90b3e47068e747c7be958d22fb56fe4f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "90bde27c6e564ca285a65d6b594d6865": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "95c3ba1f3cef4ca887dd8461db595c0a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "992b23b615fb4e88a92782c64ad60cc2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_0c8b1327b27449a49f9b71fdc80d831c", "IPY_MODEL_c22392fb7cf0489caf741568e796fc9d", "IPY_MODEL_b17ceb2a58d64747aafd29836e681e02" ], "layout": "IPY_MODEL_46031a26e4ff42819f1169eb07718b46" } }, "9958cd546fbe477092527a14bb3bfe21": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6b8769a26838449e9d7d45fc5cc7a6f6", "placeholder": "", "style": "IPY_MODEL_b2a72b0caf104aee8dd95bff01cc52a4", "value": " 848/0 [00:00<00:00, 1414.45 examples/s]" } }, "9b22b13729bf4f20b8b96da540cfaa3f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_00a619827a094be4ae891726e44ddd97", "placeholder": "", "style": "IPY_MODEL_81a7889575ed4e0293f7ce56032e6edb", "value": " 149/? [00:00<00:00, 1609.27ex/s]" } }, "9c28978adf974326a21259ae56f47fe9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "9cce7704e9e74588aa7aa3b9ddf9672f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "9ea974dfe1184fe3897a7d9d031c7624": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "a27c1dd0b5c447058bf8abde274d7085": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "a33fe3bf150949fd9679ff1fe91d4433": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "a4411af1dda24dec9b863793ccd22390": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_ee8a677f68a147e5b10a35518616e264", "IPY_MODEL_315ae5446f264660bbe6119e8261495d", "IPY_MODEL_64b970adf3af40268fb60e38140157e2" ], "layout": "IPY_MODEL_f085643a56b94b74bb7e883598170f01" } }, "a968de55d2e148f88084ac96444c17ee": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "aa47a09bf444413ba95322d979c1908c": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "aab799184cf8453e9cf026a32abff619": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ae51183c24fe42809d080fd15c298f92": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ae5b0f9f37e44e8e965f7e20dfdf3bfa": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "aee17658cd4b4fe49a759ad6c9d5a576": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "info", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c0aeab2086de4ca7ad8b5f0bbcde009c", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_a968de55d2e148f88084ac96444c17ee", "value": 1 } }, "af14186997de449f997936a81d69876b": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "b17ceb2a58d64747aafd29836e681e02": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ce845667dcf54353b02299f85dcda29d", "placeholder": "", "style": "IPY_MODEL_478464758f2b455bb8848ef4046ed11d", "value": " 149/? [00:00<00:00, 1769.20ex/s]" } }, "b2a72b0caf104aee8dd95bff01cc52a4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "b9d888877a7e4a24b07f4fb91ceda179": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_4407f3810d5d4820acf8db794ce305e6", "IPY_MODEL_72fee1a44b5343a7add71c9649139317", "IPY_MODEL_9b22b13729bf4f20b8b96da540cfaa3f" ], "layout": "IPY_MODEL_36db5c636fcf46518685b91a168d9c11" } }, "c0aeab2086de4ca7ad8b5f0bbcde009c": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "c139ed75ff4d47d593f8cb5f3fa4c105": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "c22392fb7cf0489caf741568e796fc9d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_173c6246acdb4a3bbf6dce2e236499a2", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_33fffaf4bc4a405187a2dd4eaa7ffc67", "value": 1 } }, "c319fa946f3e4380864aed6d3fbb77e7": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c4b226675ad84ff29f62847767065469": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_ec67f65de50b4038ac3b01496ef56f98", "placeholder": "", "style": "IPY_MODEL_cb10ec01c16a4c50bf8e4c8aec491aa2", "value": "Downloading: 100%" } }, "c51fb67419ed47f98c5ed4ad4e33aeff": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c6c51e30cbb1472f9e1a49bc0f5bb2cc": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "c7017ddc94104c27b42658f27f275908": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8af6a305cc8a4a038f74f39e6ea8f040", "placeholder": "", "style": "IPY_MODEL_832b4fcaf152402e84bfdaf9833d061f", "value": "Downloading: 100%" } }, "c87e36307bf84cf4970afce9e496117d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "cb10ec01c16a4c50bf8e4c8aec491aa2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "cb3b32862a12486f8625d667bb45c368": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f90669ec059249ca81a0e2c5891834db", "placeholder": "", "style": "IPY_MODEL_27d72d36fe604e5d96d6a979ed6d50ee", "value": " 63.6M/63.6M [00:03<00:00, 35.4MB/s]" } }, "cb8b0320a4794b278f86c33bbfc9825f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "ce845667dcf54353b02299f85dcda29d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ce8bb7d0fb744e7b9ce2ff35cfdbc679": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "cf1afb1025d24c1cbbb1eefd26535a26": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_aab799184cf8453e9cf026a32abff619", "placeholder": "", "style": "IPY_MODEL_4685ef4f82764fada48035b4de9af9e2", "value": "Downloading: 100%" } }, "d434124da4654ada92573070353dbce1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_63d4b794d9df49c6ab6f77f10a76861d", "placeholder": "", "style": "IPY_MODEL_61771b0bdfe543b88fc8673a510a986c", "value": "" } }, "d43443cf2579467a9cc3e9f05c607615": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "d8426e73abce4cbaa58a89aef1fce8b7": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_21c9c4302a76449784f314c15ca59bea", "IPY_MODEL_fcc23e29fde64cde92f2ae57d7cabd78", "IPY_MODEL_61ac7115c9b24ebb855343cc01b1d3f4" ], "layout": "IPY_MODEL_ae51183c24fe42809d080fd15c298f92" } }, "d8593055a0ea45f5ab13377c18e2b1e0": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_6e1517cd2bed4a35b52de6cdc812b75c", "placeholder": "", "style": "IPY_MODEL_efb5e6e4970f43d1b6197e4aaedac0b7", "value": " 1/1 [00:00<00:00, 8.08ba/s]" } }, "d9c616f1d67c4590a55bf797d8ab1904": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_002decc6fb504205ae9f61a4871e1532", "placeholder": "", "style": "IPY_MODEL_c6c51e30cbb1472f9e1a49bc0f5bb2cc", "value": " 1/1 [00:00<00:00, 19.32ba/s]" } }, "da3f94cc1140466cbcbdb3e03cbea8c2": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e106fee906b8408ebba822b4ff70693f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_2d251c97292c4824a6cb218548c17353", "IPY_MODEL_fcf8a57a02ec44398b95f4a64ad2f0fe", "IPY_MODEL_8aaba2878c2c484e8fbf9d81354f924f" ], "layout": "IPY_MODEL_af14186997de449f997936a81d69876b" } }, "e270b7c82f784ebbbba4b17fb07c310d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": "center", "align_self": null, "border": null, "bottom": null, "display": "flex", "flex": null, "flex_flow": "column", "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "50%" } }, "e410e7aecf23433f880a0f7169a8ce97": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e5124c5171e04625b70795e4b7a18819": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ButtonStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "button_color": null, "font_weight": "" } }, "e549178ba75f4939aba6ae1cf743722a": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e5d1a213afc04270926da41e12b30362": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_c7017ddc94104c27b42658f27f275908", "IPY_MODEL_155de8f44ddf4021a5d1d4d4968934db", "IPY_MODEL_cb3b32862a12486f8625d667bb45c368" ], "layout": "IPY_MODEL_30afb513746845b481227b3191df4c90" } }, "eba629a92467433c92840e4450e7a937": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ec67f65de50b4038ac3b01496ef56f98": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "eda7343054624f4d8a2e2b981b4fab41": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ee80362b77ef4375bb931af34bc16d07": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": "20px" } }, "ee8a677f68a147e5b10a35518616e264": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7bf164fec94c40858cf5280937f8e00a", "placeholder": "", "style": "IPY_MODEL_2ac4df7918404aed92611750471cd85f", "value": "" } }, "efb5e6e4970f43d1b6197e4aaedac0b7": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "efd0fc9b3766457484533a6eb59f2cd4": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "f085643a56b94b74bb7e883598170f01": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "f347c0838adf462d886a4ae36a3a6b41": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7fa8f65c508e4e629b1a2212aaa64ebc", "max": 9880, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_1795d07714684311b1ccea7514f298e4", "value": 9880 } }, "f3891dcc62b74ccd8d5a61b0ca761b2a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "info", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_41515b22976648aabe660b8df3506c4c", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_3f8a5e226fbf4175b4fa7f39a2a9d290", "value": 1 } }, "f3a862eb1219484b8d9381fb0d16b063": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_2fedf1edcc184d9b8c67712511f8bfef", "IPY_MODEL_25142b9649ef403c8b37cdb7f9a8de4b", "IPY_MODEL_8f5cd0e3111241b8a61914dac82acf73" ], "layout": "IPY_MODEL_da3f94cc1140466cbcbdb3e03cbea8c2" } }, "f49c5c9c58ee482a8264e422d4610a8a": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "f56579df97b94a5a8b3a0fbf32905687": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_9ea974dfe1184fe3897a7d9d031c7624", "placeholder": "", "style": "IPY_MODEL_8148f4330d0f441998d9a3ca4942bc22", "value": "" } }, "f90669ec059249ca81a0e2c5891834db": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "fcc23e29fde64cde92f2ae57d7cabd78": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_822d95bb43c44a4394441d92e25120d7", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_07447e6083b04bfeb04e5a601fe475bd", "value": 1 } }, "fcf8a57a02ec44398b95f4a64ad2f0fe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_781d2e3803574e2c841acfd1e090b84f", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_2d63896d07f64d91abb45c257ace72db", "value": 1 } }, "fe412730e037441b961a664573d02ae7": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "fed5fdea500f46618789c44aef2bff3b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "nbformat": 4, "nbformat_minor": 4 }