readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - librispeech_asr
  model-index:
  - name: ''
    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. -->
  
  # 
  
  This model was trained from scratch on the librispeech_asr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1277
  - Wer: 1.0334
  
  ## 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: 0.0003
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 4.7015        | 0.28  | 500  | 5.3313          | 1.9454 |
  | 4.7239        | 0.56  | 1000 | 5.1316          | 1.9288 |
  | 4.6686        | 0.84  | 1500 | 4.8812          | 1.9646 |
  | 4.0138        | 1.12  | 2000 | 4.8274          | 1.8905 |
  | 3.6314        | 1.4   | 2500 | 3.8913          | 1.7298 |
  | 1.9511        | 1.68  | 3000 | 2.3486          | 1.3674 |
  | 1.212         | 1.96  | 3500 | 1.6223          | 1.1877 |
  | 0.8092        | 2.24  | 4000 | 1.3949          | 1.1049 |
  | 0.497         | 2.52  | 4500 | 1.2544          | 1.0749 |
  | 0.4401        | 2.8   | 5000 | 1.1277          | 1.0334 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  