readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-summarization
  language: en
  datasets:
  - how2
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `espnet/roshansh_how2_asr_raw_ft_sum_valid.acc`
  
  This model was trained by roshansh-cmu using how2 recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  git checkout e6f42a9783a5d9eba0687c19417f933e890722d7
  pip install -e .
  cd egs2/how2/sum1
  ./run.sh --skip_data_prep false --skip_train true --download_model espnet/roshansh_how2_asr_raw_ft_sum_valid.acc
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Mon Feb  7 15:24:21 EST 2022`
  - python version: `3.8.12 (default, Oct 12 2021, 13:49:34)  [GCC 7.5.0]`
  - espnet version: `espnet 0.10.6a1`
  - pytorch version: `pytorch 1.10.1`
  - Git hash: `04561cdf3b6c3bc1d51edb04c93b953759ef551d`
    - Commit date: `Mon Feb 7 09:06:12 2022 -0500`
  
  ## asr_raw_ft_sum
  |dataset|Snt|Wrd|ROUGE-1|ROUGE-2|ROUGE-L|METEOR|BERTScore|
  |---|---|---|---|---|---|---|---|
  |decode_sum_asr_model_valid.acc.best/dev5_test_sum|2127|69795|60.72|44.7|56.1|29.36|91.53|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/train_asr_conformer_vid_lf.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_raw_ft_sum
  ngpu: 1
  seed: 0
  num_workers: 1
  num_att_plot: 3
  dist_backend: nccl
  dist_init_method: env://
  dist_world_size: 8
  dist_rank: 0
  local_rank: 0
  dist_master_addr: localhost
  dist_master_port: 45875
  dist_launcher: null
  multiprocessing_distributed: true
  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: 10
  val_scheduler_criterion:
  - valid
  - loss
  early_stopping_criterion:
  - valid
  - loss
  - min
  best_model_criterion:
  -   - valid
      - acc
      - max
  keep_nbest_models: 10
  grad_clip: 5.0
  grad_clip_type: 2.0
  grad_noise: false
  accum_grad: 10
  no_forward_run: false
  resume: true
  train_dtype: float32
  use_amp: false
  log_interval: 5000
  use_tensorboard: true
  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:
  - exp/asr_raw_utt_conformer/valid.acc.ave_10best.pth:::ctc
  ignore_init_mismatch: false
  freeze_param: []
  num_iters_per_epoch: null
  batch_size: 20
  valid_batch_size: null
  batch_bins: 60000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_vid_sum/train/speech_shape
  - exp/asr_stats_raw_vid_sum/train/text_shape.bpe
  valid_shape_file:
  - exp/asr_stats_raw_vid_sum/valid/speech_shape
  - exp/asr_stats_raw_vid_sum/valid/text_shape.bpe
  batch_type: length
  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/tr_2000h_sum_trim/wav.scp
      - speech
      - sound
  -   - dump/raw/tr_2000h_sum_trim/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/cv05_sum_trim/wav.scp
      - speech
      - sound
  -   - dump/raw/cv05_sum_trim/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: 0.001
  scheduler: reducelronplateau
  scheduler_conf:
      mode: min
      factor: 0.5
      patience: 1
  token_list:
  - <blank>
  - <unk>
  - '[hes]'
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  - ▁DE
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  - ▁ALSO
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  - ▁HE
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  - ▁CO
  - ▁SURE
  - ▁AGAIN
  - ▁MA
  - ▁KNOW
  - IT
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  - IC
  - ▁OTHER
  - LA
  - ▁P
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  - ▁NICE
  - ▁T
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  - ▁SE
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  - ▁WORK
  - ▁THROUGH
  - ▁O
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  - ▁AROUND
  - ▁BA
  - PE
  - ▁HI
  - ▁BY
  - SH
  - ATION
  - ▁SU
  - ▁CA
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  - ▁LI
  - ▁PLAY
  - Z
  - ▁ADD
  - ▁RO
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  - AS
  - ▁FOUR
  - ▁CON
  - ▁THOSE
  - MP
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  - ▁SP
  - UT
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  - ▁WELL
  - ▁BALL
  - TING
  - RY
  - X
  - ▁HO
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  - IVE
  - ▁NEXT
  - 