readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-15epochs-3e4
    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. -->
  
  # wav2vec2-15epochs-3e4
  
  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: 0.2620
  - Wer: 0.2097
  
  ## 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: 0.0003
  - 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: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0349        | 0.36  | 100  | 0.2561          | 0.2127 |
  | 0.0248        | 0.72  | 200  | 0.2822          | 0.2133 |
  | 0.0298        | 1.08  | 300  | 0.2751          | 0.2317 |
  | 0.0459        | 1.44  | 400  | 0.3767          | 0.2538 |
  | 0.0693        | 1.8   | 500  | 0.4385          | 0.3031 |
  | 0.06          | 2.16  | 600  | 0.4180          | 0.2919 |
  | 0.0663        | 2.52  | 700  | 0.3613          | 0.2707 |
  | 0.0638        | 2.88  | 800  | 0.3703          | 0.2887 |
  | 0.0823        | 3.24  | 900  | 0.3058          | 0.2815 |
  | 0.0673        | 3.6   | 1000 | 0.3425          | 0.2793 |
  | 0.049         | 3.96  | 1100 | 0.3508          | 0.2597 |
  | 0.0588        | 4.32  | 1200 | 0.3257          | 0.2542 |
  | 0.0527        | 4.68  | 1300 | 0.3560          | 0.2660 |
  | 0.0799        | 5.04  | 1400 | 0.3480          | 0.2544 |
  | 0.0526        | 5.4   | 1500 | 0.3653          | 0.2634 |
  | 0.0688        | 5.76  | 1600 | 0.3146          | 0.2499 |
  | 0.0651        | 6.12  | 1700 | 0.3179          | 0.2479 |
  | 0.0752        | 6.47  | 1800 | 0.3011          | 0.2359 |
  | 0.0833        | 6.83  | 1900 | 0.3444          | 0.2469 |
  | 0.055         | 7.19  | 2000 | 0.3242          | 0.2438 |
  | 0.0626        | 7.55  | 2100 | 0.3166          | 0.2343 |
  | 0.0558        | 7.91  | 2200 | 0.3307          | 0.2385 |
  | 0.061         | 8.27  | 2300 | 0.3255          | 0.2304 |
  | 0.0529        | 8.63  | 2400 | 0.2864          | 0.2365 |
  | 0.0431        | 8.99  | 2500 | 0.3058          | 0.2276 |
  | 0.0737        | 9.35  | 2600 | 0.2943          | 0.2284 |
  | 0.0514        | 9.71  | 2700 | 0.3015          | 0.2277 |
  | 0.0893        | 10.07 | 2800 | 0.2709          | 0.2287 |
  | 0.0752        | 10.43 | 2900 | 0.2897          | 0.2264 |
  | 0.0604        | 10.79 | 3000 | 0.2772          | 0.2238 |
  | 0.0433        | 11.15 | 3100 | 0.2577          | 0.2188 |
  | 0.0325        | 11.51 | 3200 | 0.2671          | 0.2162 |
  | 0.0389        | 11.87 | 3300 | 0.2694          | 0.2177 |
  | 0.0487        | 12.23 | 3400 | 0.2835          | 0.2210 |
  | 0.0318        | 12.59 | 3500 | 0.2754          | 0.2153 |
  | 0.0268        | 12.95 | 3600 | 0.2668          | 0.2153 |
  | 0.0494        | 13.31 | 3700 | 0.2734          | 0.2149 |
  | 0.0645        | 13.67 | 3800 | 0.2450          | 0.2111 |
  | 0.0318        | 14.03 | 3900 | 0.2580          | 0.2099 |
  | 0.0454        | 14.39 | 4000 | 0.2656          | 0.2092 |
  | 0.0187        | 14.75 | 4100 | 0.2620          | 0.2097 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.9.0
  - Tokenizers 0.10.3
  