python -m torch.distributed.launch \ --nproc_per_node=8 \ ./examples/research_projects/xtreme-s/run_xtreme_s.py \ --model_name_or_path="facebook/wav2vec2-xls-r-300m" \ --task="fleurs-asr" \ --language="en_us" \ --output_dir="xtreme_s_xlsr_300m_fleurs_asr_en_us_nomask" \ --overwrite_output_dir \ --num_train_epochs=30 \ --per_device_train_batch_size=8 \ --per_device_eval_batch_size=1 \ --gradient_accumulation_steps=1 \ --eval_accumulation_steps=10 \ --learning_rate="3e-4" \ --ctc_zero_infinity \ --warmup_steps=200 \ --evaluation_strategy="steps" \ --max_duration_in_seconds=20 \ --preprocessing_num_workers=16 \ --logging_steps=1 \ --eval_steps=200 \ --layerdrop=0.0 \ --mask_time_prob=0.05 \ --mask_time_length=10 \ --mask_feature_prob=0.05 \ --mask_feature_length=64 \ --freeze_feature_encoder \ --gradient_checkpointing \ --fp16 \ --fp16_full_eval \ --group_by_length \ --do_train \ --do_predict \ --per_lang_metrics=False \ --push_to_hub