readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0-Temp-1-mse
    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. -->
  
  # libri-alpha-0-Temp-1-mse
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.7799
  - Wer: 0.2824
  
  ## 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: 2e-05
  - train_batch_size: 28
  - eval_batch_size: 28
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 56
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 23.5935       | 0.65  | 100  | 14.9492         | 0.2308 |
  | 13.2557       | 1.31  | 200  | 5.0349          | 0.6077 |
  | 9.9465        | 1.96  | 300  | 4.5289          | 0.5263 |
  | 8.8716        | 2.61  | 400  | 4.1278          | 0.4377 |
  | 8.2434        | 3.27  | 500  | 4.0123          | 0.4013 |
  | 7.8993        | 3.92  | 600  | 3.8645          | 0.3500 |
  | 7.554         | 4.58  | 700  | 4.0048          | 0.3276 |
  | 7.3348        | 5.23  | 800  | 3.8652          | 0.3212 |
  | 7.1906        | 5.88  | 900  | 3.7930          | 0.3101 |
  | 6.9957        | 6.54  | 1000 | 3.4559          | 0.2958 |
  | 6.9153        | 7.19  | 1100 | 3.7799          | 0.2824 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  