readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-10epochs-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. -->
  
  # wav2vec2-10epochs-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: 0.3076
  - Wer: 0.2157
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.1184        | 0.36  | 100  | 0.4169          | 0.3008 |
  | 0.0747        | 0.72  | 200  | 0.3413          | 0.2677 |
  | 0.046         | 1.08  | 300  | 0.3245          | 0.2496 |
  | 0.0263        | 1.44  | 400  | 0.3094          | 0.2450 |
  | 0.0326        | 1.8   | 500  | 0.3031          | 0.2366 |
  | 0.0179        | 2.16  | 600  | 0.2966          | 0.2324 |
  | 0.0209        | 2.52  | 700  | 0.2920          | 0.2287 |
  | 0.0095        | 2.88  | 800  | 0.2966          | 0.2267 |
  | 0.0113        | 3.24  | 900  | 0.2997          | 0.2259 |
  | 0.0107        | 3.6   | 1000 | 0.3011          | 0.2221 |
  | 0.009         | 3.96  | 1100 | 0.3050          | 0.2219 |
  | 0.0131        | 4.32  | 1200 | 0.3034          | 0.2195 |
  | 0.0147        | 4.68  | 1300 | 0.3042          | 0.2204 |
  | 0.0195        | 5.04  | 1400 | 0.3187          | 0.2204 |
  | 0.0087        | 5.4   | 1500 | 0.3205          | 0.2198 |
  | 0.0083        | 5.76  | 1600 | 0.3177          | 0.2197 |
  | 0.016         | 6.12  | 1700 | 0.3110          | 0.2175 |
  | 0.0152        | 6.47  | 1800 | 0.3078          | 0.2171 |
  | 0.0173        | 6.83  | 1900 | 0.3134          | 0.2169 |
  | 0.046         | 7.19  | 2000 | 0.3134          | 0.2164 |
  | 0.0264        | 7.55  | 2100 | 0.3095          | 0.2174 |
  | 0.0143        | 7.91  | 2200 | 0.3066          | 0.2170 |
  | 0.0186        | 8.27  | 2300 | 0.3086          | 0.2181 |
  | 0.0308        | 8.63  | 2400 | 0.3103          | 0.2175 |
  | 0.0246        | 8.99  | 2500 | 0.3083          | 0.2157 |
  | 0.0126        | 9.35  | 2600 | 0.3073          | 0.2154 |
  | 0.0134        | 9.71  | 2700 | 0.3076          | 0.2157 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.1
  - Datasets 2.9.0
  - Tokenizers 0.10.3
  