readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xlsr-53_toy_train_fast_masked_augment_random_noise_slow_fast
    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_fast_masked_augment_random_noise_slow_fast
  
  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: 0.4007
  - Wer: 0.3785
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.0535        | 1.2   | 500  | 3.3994          | 0.9954 |
  | 1.1495        | 2.4   | 1000 | 0.6490          | 0.7155 |
  | 0.7148        | 3.6   | 1500 | 0.3812          | 0.4690 |
  | 0.5305        | 4.8   | 2000 | 0.3529          | 0.4373 |
  | 0.475         | 6.0   | 2500 | 0.3616          | 0.4123 |
  | 0.3772        | 7.19  | 3000 | 0.3823          | 0.4074 |
  | 0.3632        | 8.39  | 3500 | 0.3665          | 0.3929 |
  | 0.3579        | 9.59  | 4000 | 0.3838          | 0.3917 |
  | 0.3386        | 10.79 | 4500 | 0.3888          | 0.3839 |
  | 0.3193        | 11.99 | 5000 | 0.3872          | 0.3757 |
  | 0.2976        | 13.19 | 5500 | 0.3986          | 0.3785 |
  | 0.2915        | 14.39 | 6000 | 0.4007          | 0.3785 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu102
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  