readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att
    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-att
  
  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: 43.3741
  - Wer: 0.4535
  
  ## 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: 0.002
  - train_batch_size: 8
  - eval_batch_size: 1
  - 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_ratio: 0.2
  - num_epochs: 40
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 1062.9452     | 0.45  | 400  | 45.3735         | 0.5247 |
  | 938.9115      | 0.9   | 800  | 42.2431         | 0.4830 |
  | 838.9108      | 1.35  | 1200 | 40.3582         | 0.4517 |
  | 815.9835      | 1.79  | 1600 | 39.1145         | 0.4403 |
  | 815.1952      | 2.24  | 2000 | 40.4637         | 0.4417 |
  | 783.388       | 2.69  | 2400 | 39.3749         | 0.4312 |
  | 786.6658      | 3.14  | 2800 | 41.7742         | 0.4450 |
  | 785.0494      | 3.59  | 3200 | 42.3615         | 0.4562 |
  | 808.8199      | 4.04  | 3600 | 43.4402         | 0.4527 |
  | 765.5683      | 4.48  | 4000 | 43.2136         | 0.4505 |
  | 803.3544      | 4.93  | 4400 | 43.3741         | 0.4535 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  