readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xls-r-53m-gl-jupyter2
    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-xls-r-53m-gl-jupyter2
  
  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: 0.0941
  - Wer: 0.0615
  
  ## 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: 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: 500
  - num_epochs: 45
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.7298        | 3.36  | 400  | 0.2477          | 0.2493 |
  | 0.1507        | 6.72  | 800  | 0.1294          | 0.1264 |
  | 0.066         | 10.08 | 1200 | 0.1235          | 0.1161 |
  | 0.0456        | 13.44 | 1600 | 0.1011          | 0.1001 |
  | 0.0347        | 16.8  | 2000 | 0.1033          | 0.0909 |
  | 0.0284        | 20.17 | 2400 | 0.1083          | 0.0861 |
  | 0.0221        | 23.53 | 2800 | 0.1010          | 0.0761 |
  | 0.0199        | 26.89 | 3200 | 0.0911          | 0.0754 |
  | 0.0155        | 30.25 | 3600 | 0.1026          | 0.0743 |
  | 0.0142        | 33.61 | 4000 | 0.1024          | 0.0719 |
  | 0.0125        | 36.97 | 4400 | 0.0977          | 0.0676 |
  | 0.0104        | 40.33 | 4800 | 0.0945          | 0.0664 |
  | 0.0089        | 43.69 | 5200 | 0.0941          | 0.0615 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  