readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: librispeech-100h-supervised-meta
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # librispeech-100h-supervised-meta
  
  This model is a fine-tuned version of [Kuray107/librispeech-5h-supervised](https://huggingface.co/Kuray107/librispeech-5h-supervised) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0965
  - Wer: 0.0330
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.1131        | 1.12  | 1000  | 0.0755          | 0.0487 |
  | 0.0725        | 2.24  | 2000  | 0.0637          | 0.0404 |
  | 0.0539        | 3.36  | 3000  | 0.0661          | 0.0389 |
  | 0.0441        | 4.48  | 4000  | 0.0637          | 0.0371 |
  | 0.0379        | 5.61  | 5000  | 0.0675          | 0.0356 |
  | 0.0341        | 6.73  | 6000  | 0.0735          | 0.0360 |
  | 0.0295        | 7.85  | 7000  | 0.0737          | 0.0362 |
  | 0.0265        | 8.97  | 8000  | 0.0741          | 0.0350 |
  | 0.0244        | 10.09 | 9000  | 0.0779          | 0.0337 |
  | 0.0217        | 11.21 | 10000 | 0.0835          | 0.0343 |
  | 0.0203        | 12.33 | 11000 | 0.0785          | 0.0339 |
  | 0.0188        | 13.45 | 12000 | 0.0827          | 0.0344 |
  | 0.0179        | 14.57 | 13000 | 0.0875          | 0.0332 |
  | 0.0169        | 15.7  | 14000 | 0.0860          | 0.0330 |
  | 0.0158        | 16.82 | 15000 | 0.0954          | 0.0330 |
  | 0.0147        | 17.94 | 16000 | 0.0934          | 0.0329 |
  | 0.0148        | 19.06 | 17000 | 0.0965          | 0.0330 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.2
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  