readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - librilight_limited
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `simpleoier/simpleoier_librilight_limited_asr_train_asr_hubert_base_10h_finetuning_raw_en_char`
  
  This model was trained by simpleoier using librilight_limited recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
  if you haven't done that already.
  
  ```bash
  cd espnet
  git checkout 6752c23c61c95c9c8ba8547eab14cbd9b38d18e7
  pip install -e .
  cd egs2/librilight_limited/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model simpleoier/simpleoier_librilight_limited_asr_train_asr_hubert_base_10h_finetuning_raw_en_char
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Tue Jan 10 17:33:54 EST 2023`
  - python version: `3.9.15 (main, Nov  4 2022, 16:13:54)  [GCC 11.2.0]`
  - espnet version: `espnet 202209`
  - pytorch version: `pytorch 1.12.1`
  - Git hash: ``
    - Commit date: ``
  
  ## asr_train_asr_hubert_base_10h_finetuning_raw_en_char
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_model_valid.loss.ave/dev_clean|2694|53635|90.3|9.3|0.5|0.7|10.4|74.8|
  |decode_asr_model_valid.loss.ave/dev_other|2864|50948|83.8|15.1|1.1|1.2|17.4|83.9|
  |decode_asr_model_valid.loss.ave/test_clean|2620|52576|90.2|9.4|0.4|0.7|10.5|75.2|
  |decode_asr_model_valid.loss.ave/test_other|2939|52343|83.6|15.2|1.1|1.3|17.6|85.3|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_model_valid.loss.ave/dev_clean|2694|284127|97.8|1.2|1.0|0.8|3.0|74.8|
  |decode_asr_model_valid.loss.ave/dev_other|2864|265951|95.4|2.5|2.0|1.5|6.1|83.9|
  |decode_asr_model_valid.loss.ave/test_clean|2620|281530|97.8|1.2|1.0|0.8|3.0|75.2|
  |decode_asr_model_valid.loss.ave/test_other|2939|272758|95.5|2.5|2.0|1.6|6.1|85.3|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_hubert_base_10h_finetuning.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_hubert_base_10h_finetuning_raw_en_char
  ngpu: 1
  seed: 0
  num_workers: 1
  num_att_plot: 3
  dist_backend: nccl
  dist_init_method: env://
  dist_world_size: null
  dist_rank: null
  local_rank: 0
  dist_master_addr: null
  dist_master_port: null
  dist_launcher: null
  multiprocessing_distributed: false
  unused_parameters: true
  sharded_ddp: false
  cudnn_enabled: true
  cudnn_benchmark: false
  cudnn_deterministic: true
  collect_stats: false
  write_collected_feats: false
  max_epoch: 100
  patience: null
  val_scheduler_criterion:
  - valid
  - loss
  early_stopping_criterion:
  - valid
  - loss
  - min
  best_model_criterion:
  -   - valid
      - loss
      - min
  keep_nbest_models: 10
  nbest_averaging_interval: 0
  grad_clip: 5.0
  grad_clip_type: 2.0
  grad_noise: false
  accum_grad: 1
  no_forward_run: false
  resume: true
  train_dtype: float32
  use_amp: false
  log_interval: null
  use_matplotlib: true
  use_tensorboard: true
  create_graph_in_tensorboard: false
  use_wandb: false
  wandb_project: null
  wandb_id: null
  wandb_entity: null
  wandb_name: null
  wandb_model_log_interval: -1
  detect_anomaly: false
  pretrain_path: null
  init_param:
  - ../../librispeech/ssl1/exp/hubert_iter1_train_ssl_torchaudiohubert_base_960h_pretrain_it1_raw/valid.loss.ave.pth:encoder:encoder
  ignore_init_mismatch: false
  freeze_param: []
  num_iters_per_epoch: null
  batch_size: 20
  valid_batch_size: null
  batch_bins: 3200000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_char/train/speech_shape
  - exp/asr_stats_raw_en_char/train/text_shape.char
  valid_shape_file:
  - exp/asr_stats_raw_en_char/valid/speech_shape
  - exp/asr_stats_raw_en_char/valid/text_shape.char
  batch_type: numel
  valid_batch_type: null
  fold_length:
  - 80000
  - 150
  sort_in_batch: descending
  sort_batch: descending
  multiple_iterator: false
  chunk_length: 500
  chunk_shift_ratio: 0.5
  num_cache_chunks: 1024
  train_data_path_and_name_and_type:
  -   - dump/raw/train_10h/wav.scp
      - speech
      - sound
  -   - dump/raw/train_10h/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev_clean/wav.scp
      - speech
      - sound
  -   - dump/raw/dev_clean/text
      - text
      - text
  allow_variable_data_keys: false
  max_cache_size: 0.0
  max_cache_fd: 32
  valid_max_cache_size: null
  optim: adam
  optim_conf:
      lr: 5.0e-05
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 8000
  token_list:
  - <blank>
  - <unk>
  - <space>
  - E
  - T
  - A
  - O
  - N
  - I
  - H
  - S
  - R
  - D
  - L
  - U
  - M
  - W
  - C
  - F
  - G
  - Y
  - P
  - B
  - V
  - K
  - ''''
  - X
  - J
  - Q
  - Z
  - <sos/eos>
  init: xavier_uniform
  input_size: 1
  ctc_conf:
      dropout_rate: 0.0
      ctc_type: builtin
      reduce: true
      ignore_nan_grad: null
      zero_infinity: true
  joint_net_conf: null
  use_preprocessor: true
  token_type: char
  bpemode