readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-53_toy_train_data
    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-large-xlsr-53_toy_train_data
  
  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: 0.6357
  - Wer: 0.5496
  
  ## 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
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6073        | 2.1   | 250  | 3.5111          | 1.0    |
  | 3.0828        | 4.2   | 500  | 3.5133          | 1.0    |
  | 1.9969        | 6.3   | 750  | 1.3924          | 0.9577 |
  | 0.9279        | 8.4   | 1000 | 0.8378          | 0.7243 |
  | 0.6692        | 10.5  | 1250 | 0.7367          | 0.6394 |
  | 0.5273        | 12.6  | 1500 | 0.6703          | 0.5907 |
  | 0.4314        | 14.7  | 1750 | 0.6594          | 0.5718 |
  | 0.3809        | 16.8  | 2000 | 0.6138          | 0.5559 |
  | 0.3934        | 18.9  | 2250 | 0.6357          | 0.5496 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  