readme: ---
  language:
  - en
  tags:
  - esc
  datasets:
  - ami
  ---
  To reproduce this run, execute: 
  ```python 
  #!/usr/bin/env bash
  python run_flax_speech_recognition_seq2seq.py \
          --dataset_name="esc-benchmark/esc-datasets" \
          --model_name_or_path="esc-benchmark/wav2vec2-aed-pretrained" \
          --dataset_config_name="ami" \
          --output_dir="./" \
          --wandb_name="wav2vec2-aed-ami" \
          --wandb_project="wav2vec2-aed" \
          --per_device_train_batch_size="8" \
          --per_device_eval_batch_size="4" \
          --learning_rate="1e-4" \
          --warmup_steps="500" \
          --logging_steps="25" \
          --max_steps="50001" \
          --eval_steps="10000" \
          --save_steps="10000" \
          --generation_max_length="40" \
          --generation_num_beams="1" \
          --final_generation_max_length="225" \
          --final_generation_num_beams="5" \
          --generation_length_penalty="1.4" \
          --hidden_dropout="0.2" \
          --activation_dropout="0.2" \
          --feat_proj_dropout="0.2" \
          --overwrite_output_dir \
          --gradient_checkpointing \
          --freeze_feature_encoder \
          --predict_with_generate \
          --do_eval \
          --do_train \
          --do_predict \
          --push_to_hub \
          --use_auth_token
  ```
  