readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-53_toy_train_data_random_low_pass
    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_random_low_pass
  
  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: 0.6572
  - Wer: 0.4973
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0834        | 2.1   | 500  | 3.4478          | 1.0    |
  | 1.0735        | 4.2   | 1000 | 0.9113          | 0.7815 |
  | 0.5516        | 6.3   | 1500 | 0.7035          | 0.6081 |
  | 0.4023        | 8.4   | 2000 | 0.6647          | 0.5649 |
  | 0.3423        | 10.5  | 2500 | 0.6613          | 0.5450 |
  | 0.2938        | 12.6  | 3000 | 0.6967          | 0.5318 |
  | 0.2902        | 14.7  | 3500 | 0.6430          | 0.5089 |
  | 0.2372        | 16.81 | 4000 | 0.6653          | 0.5045 |
  | 0.2148        | 18.91 | 4500 | 0.6572          | 0.4973 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.0.0
  - Tokenizers 0.12.0
  