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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 |