readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse-take-3
    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-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse-take-3
  
  This model is a fine-tuned version of [rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse](https://huggingface.co/rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 28.9263
  - Wer: 0.3301
  
  ## 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: 0.0005
  - train_batch_size: 4
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.2
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 291.1088      | 0.22  | 400  | 28.4207         | 0.3362 |
  | 284.1968      | 0.45  | 800  | 28.1458         | 0.3314 |
  | 288.1414      | 0.67  | 1200 | 28.1397         | 0.3326 |
  | 290.0272      | 0.9   | 1600 | 28.4186         | 0.3323 |
  | 287.3224      | 1.12  | 2000 | 28.3548         | 0.3283 |
  | 279.1482      | 1.35  | 2400 | 28.5373         | 0.3309 |
  | 285.8217      | 1.57  | 2800 | 28.4447         | 0.3301 |
  | 282.9265      | 1.79  | 3200 | 28.5379         | 0.3365 |
  | 292.6254      | 2.02  | 3600 | 28.2632         | 0.3299 |
  | 279.215       | 2.24  | 4000 | 28.9263         | 0.3301 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  