readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-latino40
    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. -->
  
  # wav2vec2-latino40
  
  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: 2.8795
  - Wer: 1.0
  
  ## 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: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer |
  |:-------------:|:-----:|:----:|:---------------:|:---:|
  | 5.6846        | 0.83  | 100  | 2.9086          | 1.0 |
  | 2.8686        | 1.67  | 200  | 2.8922          | 1.0 |
  | 2.8805        | 2.5   | 300  | 2.9326          | 1.0 |
  | 2.8613        | 3.33  | 400  | 2.8698          | 1.0 |
  | 2.8643        | 4.17  | 500  | 2.9027          | 1.0 |
  | 2.8688        | 5.0   | 600  | 2.9544          | 1.0 |
  | 2.8689        | 5.83  | 700  | 2.8914          | 1.0 |
  | 2.8558        | 6.67  | 800  | 2.8762          | 1.0 |
  | 2.8537        | 7.5   | 900  | 2.8982          | 1.0 |
  | 2.8522        | 8.33  | 1000 | 2.8820          | 1.0 |
  | 2.8468        | 9.17  | 1100 | 2.8760          | 1.0 |
  | 2.8454        | 10.0  | 1200 | 2.8795          | 1.0 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.9.1
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  