| export WANDB_PROJECT="xls-r-basque" | |
| export CUDA_VISIBLE_DEVICES=2 | |
| python src/run_speech_recognition_ctc_bnb.py \ | |
| --dataset_name="mozilla-foundation/common_voice_8_0" \ | |
| --model_name_or_path="facebook/wav2vec2-xls-r-300m" \ | |
| --dataset_config_name="eu" \ | |
| --output_dir="./" \ | |
| --overwrite_output_dir \ | |
| --num_train_epochs=100 \ | |
| --per_device_train_batch_size=72 \ | |
| --per_device_eval_batch_size=72 \ | |
| --gradient_accumulation_steps=2 \ | |
| --learning_rate=3e-4 \ | |
| --save_total_limit=1 \ | |
| --warmup_steps=500 \ | |
| --evaluation_strategy=steps \ | |
| --text_column_name=sentence \ | |
| --length_column_name=input_length \ | |
| --save_steps=500 \ | |
| --eval_steps=500 \ | |
| --logging_steps=100 \ | |
| --layerdrop=0.0 \ | |
| --freeze_feature_encoder \ | |
| --feat_proj_dropout=0.1 \ | |
| --chars_to_ignore , ? . ! \- \; \: \" β % β β οΏ½ β β β¦ β \ | |
| --gradient_checkpointing \ | |
| --lr_scheduler_type=cosine \ | |
| --fp16 \ | |
| --group_by_length \ | |
| --mask_time_prob=0.1 \ | |
| --mask_time_length=10 \ | |
| --report_to=wandb \ | |
| --run_name="cosine+drop_proj+low_specaugment-300M+cv_8_0" \ | |
| --do_train --do_eval \ | |
| --use_auth_token --push_to_hub | |