readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-xlsr-53-torgo-origin-parameters-checkpoint3750
    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-origin-parameters-checkpoint3750
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the Torgo dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2104
  - Cer: 0.3903
  
  ## 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: 4
  - 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 0.63  | 250  | 19.6794         | 0.9961 |
  | 25.0027       | 1.26  | 500  | 5.6998          | 0.9961 |
  | 25.0027       | 1.89  | 750  | 5.3298          | 0.9961 |
  | 3.7083        | 2.53  | 1000 | 4.9012          | 0.9961 |
  | 3.7083        | 3.16  | 1250 | 4.7392          | 0.9961 |
  | 3.3223        | 3.79  | 1500 | 3.8672          | 0.9961 |
  | 3.3223        | 4.42  | 1750 | 2.5696          | 0.8772 |
  | 2.564         | 5.05  | 2000 | 2.0229          | 0.7136 |
  | 2.564         | 5.68  | 2250 | 1.6933          | 0.5332 |
  | 1.7148        | 6.31  | 2500 | 1.4409          | 0.4808 |
  | 1.7148        | 6.94  | 2750 | 1.3612          | 0.4601 |
  | 1.3384        | 7.58  | 3000 | 1.3402          | 0.4328 |
  | 1.3384        | 8.21  | 3250 | 1.2438          | 0.4070 |
  | 1.1197        | 8.84  | 3500 | 1.2251          | 0.3938 |
  | 1.1197        | 9.47  | 3750 | 1.2104          | 0.3903 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.12.1
  