run.sh

python $1run_speech_recognition_seq2seq_streaming.py \
	--model_name_or_path="openai/whisper-medium" \
	--dataset_train_name="mozilla-foundation/common_voice_11_0,mozilla-foundation/common_voice_11_0,mozilla-foundation/common_voice_11_0,babelbox/babelbox_voice,NbAiLab/NST,NbAiLab/NPSC,google/fleurs,google/fleurs,google/fleurs" \
	--dataset_train_config_name="sv-SE,da,nn-NO,nst,no-distant,16K_mp3_nynorsk,sv_se,da_dk,nb_no" \
	--language_train="sv,da,no,sv,no,no,sv,da,no" \
	--train_split_name="train+validation,train+validation,train+validation,train,train+test,train+validation,train+validation,train+validation,train+validation" \
	--dataset_eval_name="mozilla-foundation/common_voice_11_0" \
	--dataset_eval_config_name="sv-SE" \
	--language_eval="sv" \
	--eval_split_name="test" \
	--model_index_name="Whisper Medium Nordic" \
	--max_steps="10000" \
	--output_dir="./" \
	--per_device_train_batch_size="32" \
	--per_device_eval_batch_size="16" \
	--logging_steps="25" \
	--learning_rate="3e-6" \
	--warmup_ratio="0.1" \
	--evaluation_strategy="steps" \
	--eval_steps="1000" \
	--save_strategy="steps" \
	--save_steps="1000" \
	--generation_max_length="225" \
	--length_column_name="input_length" \
	--max_duration_in_seconds="30" \
	--text_column_name="sentence,text,raw_transcription" \
	--freeze_feature_encoder="False" \
	--report_to="wandb" \
	--save_total_limit="2" \
	--metric_for_best_model="wer" \
	--greater_is_better="False" \
	--load_best_model_at_end \
	--gradient_checkpointing \
	--overwrite_output_dir \
	--do_train \
	--do_eval \
	--fp16 \
	--predict_with_generate \
	--do_normalize_eval \
	--streaming \
	--use_auth_token