readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xls-r-300m-gl-jupyter9
    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-300m-gl-jupyter9
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0970
  - Wer: 0.0624
  
  ## 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: 60
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.6977        | 3.36  | 400  | 0.4273          | 0.4574 |
  | 0.2282        | 6.72  | 800  | 0.1492          | 0.1723 |
  | 0.0884        | 10.08 | 1200 | 0.1344          | 0.1336 |
  | 0.0594        | 13.44 | 1600 | 0.1329          | 0.1238 |
  | 0.0437        | 16.8  | 2000 | 0.1137          | 0.1153 |
  | 0.0384        | 20.17 | 2400 | 0.1197          | 0.1033 |
  | 0.0332        | 23.53 | 2800 | 0.1147          | 0.0980 |
  | 0.0282        | 26.89 | 3200 | 0.1079          | 0.0917 |
  | 0.0236        | 30.25 | 3600 | 0.1144          | 0.0922 |
  | 0.0237        | 33.61 | 4000 | 0.1130          | 0.0880 |
  | 0.019         | 36.97 | 4400 | 0.1035          | 0.0818 |
  | 0.0164        | 40.33 | 4800 | 0.1045          | 0.0813 |
  | 0.0146        | 43.69 | 5200 | 0.1037          | 0.0735 |
  | 0.0111        | 47.06 | 5600 | 0.1085          | 0.0701 |
  | 0.0093        | 50.42 | 6000 | 0.1039          | 0.0659 |
  | 0.0084        | 53.78 | 6400 | 0.0970          | 0.0636 |
  | 0.0073        | 57.14 | 6800 | 0.0970          | 0.0624 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  