readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-5epochs-3e5
    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. -->
  
  # wav2vec2-5epochs-3e5
  
  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: 0.3061
  - Wer: 0.2184
  
  ## 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: 3e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0438        | 0.36  | 100  | 0.2924          | 0.2284 |
  | 0.01          | 0.72  | 200  | 0.3055          | 0.2282 |
  | 0.0059        | 1.08  | 300  | 0.3225          | 0.2278 |
  | 0.0028        | 1.44  | 400  | 0.3393          | 0.2245 |
  | 0.0039        | 1.8   | 500  | 0.3506          | 0.2247 |
  | 0.0072        | 2.16  | 600  | 0.3605          | 0.2231 |
  | 0.0077        | 2.52  | 700  | 0.3535          | 0.2228 |
  | 0.0077        | 2.88  | 800  | 0.3267          | 0.2235 |
  | 0.01          | 3.24  | 900  | 0.3117          | 0.2229 |
  | 0.0074        | 3.6   | 1000 | 0.3061          | 0.2208 |
  | 0.0074        | 3.96  | 1100 | 0.3086          | 0.2199 |
  | 0.0108        | 4.32  | 1200 | 0.3074          | 0.2180 |
  | 0.0137        | 4.68  | 1300 | 0.3061          | 0.2184 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.9.0
  - Tokenizers 0.10.3
  