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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# HuggingFace challenge - Debugger notebook\n",
"Run this notebook to verify your libraries versions, check GPU config and run a quick training"
]
},
{
"cell_type": "code",
"execution_count": 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": {},
"source": [
"## Print main infos"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Check your GPU informations (if any)\n",
"If you launched an AI Training job with GPU resources, they should be listed below (Tesla V100s 32GB).\n",
"Driver and CUDA version "
]
},
{
"cell_type": "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": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "fevoJD15u4Ss",
"outputId": "5861d34e-745b-45ee-e780-ed363043e655"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2022-01-31 17:09:10-- https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py\n",
"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.110.133, ...\n",
"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 30360 (30K) [text/plain]\n",
"Saving to: ‘run_speech_recognition_ctc.py’\n",
"\n",
"run_speech_recognit 100%[===================>] 29.65K --.-KB/s in 0.001s \n",
"\n",
"2022-01-31 17:09:10 (55.6 MB/s) - ‘run_speech_recognition_ctc.py’ saved [30360/30360]\n",
"\n"
]
}
],
"source": [
"!wget -O run_speech_recognition_ctc.py https://raw.githubusercontent.com/huggingface/transformers/master/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Mz4bubhxxsad",
"outputId": "23398525-cc19-43c2-9fec-497e06214f29"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"01/31/2022 17:10:15 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True\n",
"01/31/2022 17:10:15 - INFO - __main__ - Training/evaluation parameters TrainingArguments(\n",
"_n_gpu=1,\n",
"adafactor=False,\n",
"adam_beta1=0.9,\n",
"adam_beta2=0.999,\n",
"adam_epsilon=1e-08,\n",
"bf16=False,\n",
"bf16_full_eval=False,\n",
"dataloader_drop_last=False,\n",
"dataloader_num_workers=0,\n",
"dataloader_pin_memory=True,\n",
"ddp_bucket_cap_mb=None,\n",
"ddp_find_unused_parameters=None,\n",
"debug=[],\n",
"deepspeed=None,\n",
"disable_tqdm=False,\n",
"do_eval=True,\n",
"do_predict=False,\n",
"do_train=True,\n",
"eval_accumulation_steps=None,\n",
"eval_steps=500,\n",
"evaluation_strategy=IntervalStrategy.STEPS,\n",
"fp16=True,\n",
"fp16_backend=auto,\n",
"fp16_full_eval=False,\n",
"fp16_opt_level=O1,\n",
"gradient_accumulation_steps=1,\n",
"gradient_checkpointing=True,\n",
"greater_is_better=None,\n",
"group_by_length=True,\n",
"half_precision_backend=auto,\n",
"hub_model_id=None,\n",
"hub_strategy=HubStrategy.EVERY_SAVE,\n",
"hub_token=<HUB_TOKEN>,\n",
"ignore_data_skip=False,\n",
"label_names=None,\n",
"label_smoothing_factor=0.0,\n",
"learning_rate=0.0003,\n",
"length_column_name=input_length,\n",
"load_best_model_at_end=False,\n",
"local_rank=-1,\n",
"log_level=-1,\n",
"log_level_replica=-1,\n",
"log_on_each_node=True,\n",
"logging_dir=./runs/Jan31_17-10-15_job-6a6be32c-c82d-4385-805b-1f7606124d5b,\n",
"logging_first_step=False,\n",
"logging_nan_inf_filter=True,\n",
"logging_steps=500,\n",
"logging_strategy=IntervalStrategy.STEPS,\n",
"lr_scheduler_type=SchedulerType.LINEAR,\n",
"max_grad_norm=1.0,\n",
"max_steps=10,\n",
"metric_for_best_model=None,\n",
"mp_parameters=,\n",
"no_cuda=False,\n",
"num_train_epochs=3.0,\n",
"optim=OptimizerNames.ADAMW_HF,\n",
"output_dir=./,\n",
"overwrite_output_dir=True,\n",
"past_index=-1,\n",
"per_device_eval_batch_size=8,\n",
"per_device_train_batch_size=2,\n",
"prediction_loss_only=False,\n",
"push_to_hub=True,\n",
"push_to_hub_model_id=None,\n",
"push_to_hub_organization=None,\n",
"push_to_hub_token=<PUSH_TO_HUB_TOKEN>,\n",
"remove_unused_columns=True,\n",
"report_to=[],\n",
"resume_from_checkpoint=None,\n",
"run_name=./,\n",
"save_on_each_node=False,\n",
"save_steps=5,\n",
"save_strategy=IntervalStrategy.STEPS,\n",
"save_total_limit=1,\n",
"seed=42,\n",
"sharded_ddp=[],\n",
"skip_memory_metrics=True,\n",
"tf32=None,\n",
"tpu_metrics_debug=False,\n",
"tpu_num_cores=None,\n",
"use_legacy_prediction_loop=False,\n",
"warmup_ratio=0.0,\n",
"warmup_steps=0,\n",
"weight_decay=0.0,\n",
"xpu_backend=None,\n",
")\n",
"Downloading: 100%|█████████████████████████| 10.1k/10.1k [00:00<00:00, 7.28MB/s]\n",
"Downloading: 100%|█████████████████████████| 2.98k/2.98k [00:00<00:00, 3.39MB/s]\n",
"Downloading: 100%|██████████████████████████| 53.1k/53.1k [00:00<00:00, 325kB/s]\n",
"Downloading and preparing dataset common_voice/ab to /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/ab/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8...\n",
"Downloading: 100%|█████████████████████████| 1.72G/1.72G [01:31<00:00, 18.8MB/s]\n",
"9124 examples [00:13, 710.66 examples/s] "
]
}
],
"source": [
"!python run_speech_recognition_ctc.py \\\n",
"\t--dataset_name=\"mozilla-foundation/common_voice_8_0\" \\\n",
"\t--model_name_or_path=\"hf-test/xls-r-dummy\" \\\n",
"\t--dataset_config_name=\"ab\" \\\n",
"\t--output_dir=\"./\" \\\n",
"\t--overwrite_output_dir \\\n",
"\t--max_steps=\"10\" \\\n",
"\t--per_device_train_batch_size=\"2\" \\\n",
"\t--learning_rate=\"3e-4\" \\\n",
"\t--save_total_limit=\"1\" \\\n",
"\t--evaluation_strategy=\"steps\" \\\n",
"\t--text_column_name=\"sentence\" \\\n",
"\t--length_column_name=\"input_length\" \\\n",
"\t--save_steps=\"5\" \\\n",
"\t--layerdrop=\"0.0\" \\\n",
"\t--freeze_feature_encoder \\\n",
"\t--gradient_checkpointing \\\n",
"\t--fp16 \\\n",
"\t--group_by_length \\\n",
"\t--push_to_hub \\\n",
"\t--use_auth_token \\\n",
"\t--do_train --do_eva"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"authorship_tag": "ABX9TyM3OaMlm9YQtKpl28c8gBBd",
"include_colab_link": true,
"name": "DebugOVHTransformers.ipynb",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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