readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-xlsr-53-torgo-8batch-30epochs-500steps
    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-xlsr-53-torgo-8batch-30epochs-500steps
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0747
  - Cer: 0.3015
  
  ## 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: 8
  - 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: 1000
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 25.2161       | 2.53  | 500  | 5.2319          | 0.9816 |
  | 3.649         | 5.05  | 1000 | 3.7028          | 0.9816 |
  | 2.8241        | 7.58  | 1500 | 2.0426          | 0.8802 |
  | 1.6018        | 10.1  | 2000 | 1.2611          | 0.4394 |
  | 1.0374        | 12.63 | 2500 | 1.1117          | 0.3713 |
  | 0.7962        | 15.15 | 3000 | 1.0730          | 0.3445 |
  | 0.6436        | 17.68 | 3500 | 1.1026          | 0.3309 |
  | 0.5344        | 20.2  | 4000 | 1.0734          | 0.3100 |
  | 0.4556        | 22.73 | 4500 | 1.0877          | 0.3177 |
  | 0.3992        | 25.25 | 5000 | 1.0614          | 0.3065 |
  | 0.3764        | 27.78 | 5500 | 1.0747          | 0.3015 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  