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: 6.5541
  - Wer: 1.9877
  
  ## 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: 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1.9364        | 0.28  | 500  | 6.3613          | 1.9833 |
  | 1.941         | 0.56  | 1000 | 5.6974          | 1.9746 |
  | 2.3312        | 0.84  | 1500 | 5.6979          | 1.7345 |
  | 2.8004        | 1.12  | 2000 | 6.0436          | 1.6787 |
  | 3.0003        | 1.4   | 2500 | 6.0955          | 1.7625 |
  | 2.9677        | 1.68  | 3000 | 6.2841          | 1.6731 |
  | 2.2759        | 1.96  | 3500 | 6.3094          | 1.7494 |
  | 2.2989        | 2.24  | 4000 | 6.9891          | 1.9115 |
  | 1.8814        | 2.52  | 4500 | 6.9818          | 1.9832 |
  | 2.658         | 2.8   | 5000 | 6.5541          | 1.9877 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu113
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  