readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-53_toy_train_data_augment_0.1
    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_augment_0.1
  
  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: 0.4658
  - Wer: 0.5037
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.447         | 1.05  | 250  | 3.3799          | 1.0    |
  | 3.089         | 2.1   | 500  | 3.4868          | 1.0    |
  | 3.063         | 3.15  | 750  | 3.3155          | 1.0    |
  | 2.4008        | 4.2   | 1000 | 1.2934          | 0.8919 |
  | 1.618         | 5.25  | 1250 | 0.7847          | 0.7338 |
  | 1.3038        | 6.3   | 1500 | 0.6459          | 0.6712 |
  | 1.2074        | 7.35  | 1750 | 0.5705          | 0.6269 |
  | 1.1062        | 8.4   | 2000 | 0.5267          | 0.5843 |
  | 1.026         | 9.45  | 2250 | 0.5108          | 0.5683 |
  | 0.9505        | 10.5  | 2500 | 0.5066          | 0.5568 |
  | 0.893         | 11.55 | 2750 | 0.5161          | 0.5532 |
  | 0.8535        | 12.6  | 3000 | 0.4994          | 0.5341 |
  | 0.8462        | 13.65 | 3250 | 0.4626          | 0.5262 |
  | 0.8334        | 14.7  | 3500 | 0.4593          | 0.5197 |
  | 0.842         | 15.75 | 3750 | 0.4651          | 0.5126 |
  | 0.7678        | 16.81 | 4000 | 0.4687          | 0.5120 |
  | 0.7873        | 17.86 | 4250 | 0.4716          | 0.5070 |
  | 0.7486        | 18.91 | 4500 | 0.4657          | 0.5033 |
  | 0.7073        | 19.96 | 4750 | 0.4658          | 0.5037 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  