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Training in progress, step 4000
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python run_speech_recognition_ctc.py \
--dataset_name="google/fleurs" \
--dataset_config_name="ps_af" \
--model_name_or_path="facebook/wav2vec2-xls-r-300m" \
--output_dir="./" \
--overwrite_output_dir="False" \
--max_steps="4000" \
--per_device_train_batch_size="8" \
--per_device_eval_batch_size="8" \
--gradient_accumulation_steps="4" \
--learning_rate="7.5e-5" \
--warmup_steps="2000" \
--evaluation_strategy="steps" \
--text_column_name="transcription" \
--save_steps="500" \
--eval_steps="500" \
--logging_steps="10" \
--layerdrop="0.0" \
--activation_dropout="0.1" \
--eval_metrics wer cer \
--greater_is_better="False" \
--load_best_model_at_end \
--save_total_limit="3" \
--mask_time_prob="0.3" \
--mask_time_length="10" \
--mask_feature_prob="0.1" \
--fp16 \
--mask_feature_length="64" \
--chars_to_ignore , ? . ! - \; \: \" “ % ‘ ” � \
--group_by_length \
--push_to_hub \
--do_train --do_eval \
--gradient_checkpointing \
--use_auth_token
--freeze_feature_extractor="True"