readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: w2v2-libri
    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. -->
  
  # w2v2-libri
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7315
  - Wer: 0.5574
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 3000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.1828        | 50.0  | 200  | 3.0563          | 1.0    |
  | 2.8849        | 100.0 | 400  | 2.9023          | 1.0    |
  | 1.5108        | 150.0 | 600  | 1.1468          | 0.6667 |
  | 0.1372        | 200.0 | 800  | 1.3749          | 0.6279 |
  | 0.0816        | 250.0 | 1000 | 1.3985          | 0.6224 |
  | 0.0746        | 300.0 | 1200 | 1.5285          | 0.6141 |
  | 0.0556        | 350.0 | 1400 | 1.5496          | 0.5920 |
  | 0.0644        | 400.0 | 1600 | 1.6263          | 0.5947 |
  | 0.0546        | 450.0 | 1800 | 1.6803          | 0.5906 |
  | 0.0491        | 500.0 | 2000 | 1.6155          | 0.5837 |
  | 0.0518        | 550.0 | 2200 | 1.6784          | 0.5698 |
  | 0.0314        | 600.0 | 2400 | 1.6050          | 0.5602 |
  | 0.0048        | 650.0 | 2600 | 1.7703          | 0.5546 |
  | 0.0042        | 700.0 | 2800 | 1.7135          | 0.5615 |
  | 0.0025        | 750.0 | 3000 | 1.7315          | 0.5574 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  