readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-large-xls-r-300m-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-300m-gl-jupyter7
  
  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: 0.1004
  - Wer: 0.0647
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.8074        | 3.36  | 400  | 0.4882          | 0.5245 |
  | 0.2396        | 6.72  | 800  | 0.1335          | 0.1524 |
  | 0.0876        | 10.08 | 1200 | 0.1216          | 0.1199 |
  | 0.0597        | 13.44 | 1600 | 0.1289          | 0.1241 |
  | 0.0449        | 16.8  | 2000 | 0.1164          | 0.1028 |
  | 0.0372        | 20.17 | 2400 | 0.1270          | 0.1023 |
  | 0.0319        | 23.53 | 2800 | 0.1111          | 0.0966 |
  | 0.0286        | 26.89 | 3200 | 0.1142          | 0.0925 |
  | 0.0246        | 30.25 | 3600 | 0.1142          | 0.0926 |
  | 0.0235        | 33.61 | 4000 | 0.1075          | 0.0836 |
  | 0.0181        | 36.97 | 4400 | 0.1083          | 0.0837 |
  | 0.0151        | 40.33 | 4800 | 0.1140          | 0.0768 |
  | 0.014         | 43.69 | 5200 | 0.1015          | 0.0748 |
  | 0.0111        | 47.06 | 5600 | 0.1023          | 0.0702 |
  | 0.0093        | 50.42 | 6000 | 0.1028          | 0.0708 |
  | 0.0078        | 53.78 | 6400 | 0.0999          | 0.0645 |
  | 0.0071        | 57.14 | 6800 | 0.1004          | 0.0647 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu111
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  