readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xls-r-53m-gl-jupyter7
    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-jupyter7
  
  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: 0.1000
  - Wer: 0.0639
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.8697        | 3.36  | 400  | 0.2631          | 0.2756 |
  | 0.1569        | 6.72  | 800  | 0.1243          | 0.1300 |
  | 0.0663        | 10.08 | 1200 | 0.1124          | 0.1153 |
  | 0.0468        | 13.44 | 1600 | 0.1118          | 0.1037 |
  | 0.0356        | 16.8  | 2000 | 0.1102          | 0.0978 |
  | 0.0306        | 20.17 | 2400 | 0.1095          | 0.0935 |
  | 0.0244        | 23.53 | 2800 | 0.1072          | 0.0844 |
  | 0.0228        | 26.89 | 3200 | 0.1014          | 0.0874 |
  | 0.0192        | 30.25 | 3600 | 0.1084          | 0.0831 |
  | 0.0174        | 33.61 | 4000 | 0.1048          | 0.0772 |
  | 0.0142        | 36.97 | 4400 | 0.1063          | 0.0764 |
  | 0.0131        | 40.33 | 4800 | 0.1046          | 0.0770 |
  | 0.0116        | 43.69 | 5200 | 0.0999          | 0.0716 |
  | 0.0095        | 47.06 | 5600 | 0.1044          | 0.0729 |
  | 0.0077        | 50.42 | 6000 | 0.1024          | 0.0670 |
  | 0.0071        | 53.78 | 6400 | 0.0968          | 0.0631 |
  | 0.0064        | 57.14 | 6800 | 0.1000          | 0.0639 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  