run_librispeech.sh

#!/usr/bin/env bash
python run_flax_speech_recognition_seq2seq.py \
        --dataset_name="librispeech_asr" \
        --model_name_or_path="./" \
        --dataset_config_name="all" \
        --train_split_name="train.clean.100+train.clean.360+train.other.500" \
        --eval_split_name="validation.clean" \
	--dataset_cache_dir="/home/sanchitgandhi/cache/huggingface/datasets" \
        --output_dir="./output_dir" \
        --preprocessing_num_workers="16" \
        --length_column_name="input_length" \
        --overwrite_output_dir \
        --num_train_epochs="3" \
        --per_device_train_batch_size="8" \
        --per_device_eval_batch_size="2" \
        --logging_steps="25" \
	--gradient_checkpointing \
        --max_duration_in_seconds="20" \
        --max_target_length="128" \
        --generation_max_length="40" \
        --generation_num_beams="1" \
	--final_generation_max_length="200" \
	--final_generation_num_beams="5" \
        --learning_rate="3e-4" \
        --warmup_steps="500" \
        --text_column_name="text" \
        --save_total_limit="1" \
        --freeze_feature_encoder \
        --predict_with_generate \
        --do_lower_case \
        --do_eval \
        --do_train \
        --wandb_project="flax-wav2vec2-2-bart-large-960h"