readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: model-1h
    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. -->
  
  # model-1h
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8317
  - Wer: 1.0
  
  ## 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: 5
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 11.4106       | 1.24  | 10   | 7.1597          | 1.0    |
  | 4.777         | 2.47  | 20   | 3.9782          | 1.0    |
  | 3.6585        | 3.71  | 30   | 3.3961          | 1.0    |
  | 3.3143        | 4.94  | 40   | 3.1481          | 1.0    |
  | 3.3318        | 6.24  | 50   | 3.0596          | 1.0    |
  | 3.1368        | 7.47  | 60   | 2.9751          | 1.0    |
  | 3.1058        | 8.71  | 70   | 2.9510          | 1.0    |
  | 3.0605        | 9.94  | 80   | 2.9479          | 1.0    |
  | 3.2043        | 11.24 | 90   | 2.9270          | 1.0    |
  | 3.0424        | 12.47 | 100  | 2.9349          | 1.0    |
  | 3.0374        | 13.71 | 110  | 2.9316          | 1.0    |
  | 3.0256        | 14.94 | 120  | 2.9165          | 1.0    |
  | 3.1724        | 16.24 | 130  | 2.9076          | 1.0    |
  | 3.0119        | 17.47 | 140  | 2.9034          | 1.0    |
  | 2.9937        | 18.71 | 150  | 2.8812          | 1.0    |
  | 2.9775        | 19.94 | 160  | 2.8674          | 1.0    |
  | 3.0826        | 21.24 | 170  | 2.8147          | 1.0    |
  | 2.8717        | 22.47 | 180  | 2.7212          | 1.0    |
  | 2.7714        | 23.71 | 190  | 2.6149          | 0.9952 |
  | 2.634         | 24.94 | 200  | 2.4611          | 0.9984 |
  | 2.5637        | 26.24 | 210  | 2.2734          | 1.0    |
  | 2.237         | 27.47 | 220  | 2.0705          | 1.0    |
  | 2.0381        | 28.71 | 230  | 1.9216          | 1.0    |
  | 1.8788        | 29.94 | 240  | 1.8317          | 1.0    |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu102
  - Datasets 1.18.3
  - Tokenizers 0.10.3
  