readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: libri-finetune
    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-finetune
  
  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: 349.4102
  - Wer: 0.8141
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 13179.94      | 2.99  | 400  | 5612.7529       | 1.0    |
  | 6948.38       | 5.97  | 800  | 1633.0823       | 0.9563 |
  | 2144.6125     | 8.96  | 1200 | 578.3821        | 0.8487 |
  | 1293.3905     | 11.94 | 1600 | 448.8980        | 0.8405 |
  | 955.5785      | 14.93 | 2000 | 403.0979        | 0.8327 |
  | 843.732       | 17.91 | 2400 | 374.1770        | 0.8220 |
  | 739.1473      | 20.9  | 2800 | 360.7842        | 0.8179 |
  | 651.852       | 23.88 | 3200 | 353.6803        | 0.8159 |
  | 658.5995      | 26.87 | 3600 | 350.6870        | 0.8099 |
  | 608.4441      | 29.85 | 4000 | 349.4102        | 0.8141 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  