readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: ASCEND_Dataset_Model
    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. -->
  
  # ASCEND_Dataset_Model
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.9199
  - Wer: 0.9540
  - Cer: 0.9868
  
  ## 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: 8
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
  | 16.9063       | 1.0   | 687   | 4.7768          | 1.0    | 1.0    |
  | 5.0252        | 2.0   | 1374  | 4.7004          | 1.0    | 1.0    |
  | 4.9378        | 3.0   | 2061  | 4.6715          | 1.0    | 1.0    |
  | 5.1468        | 4.0   | 2748  | 4.6605          | 1.0    | 1.0    |
  | 4.9353        | 5.0   | 3435  | 4.6470          | 1.0    | 1.0    |
  | 4.913         | 6.0   | 4122  | 4.6177          | 1.0    | 1.0    |
  | 4.8034        | 7.0   | 4809  | 4.7699          | 1.0    | 1.0    |
  | 4.6905        | 8.0   | 5496  | 4.3596          | 1.0    | 1.0    |
  | 4.5251        | 9.0   | 6183  | 4.2670          | 1.0    | 1.0    |
  | 4.4527        | 10.0  | 6870  | 4.2087          | 1.0    | 1.0    |
  | 4.3731        | 11.0  | 7557  | 4.1950          | 0.9982 | 0.9997 |
  | 4.3461        | 12.0  | 8244  | 4.2287          | 0.9928 | 0.9988 |
  | 4.3224        | 13.0  | 8931  | 4.1565          | 0.9802 | 0.9971 |
  | 4.2504        | 14.0  | 9618  | 4.1254          | 0.9619 | 0.9937 |
  | 4.2196        | 15.0  | 10305 | 4.0377          | 0.9562 | 0.9913 |
  | 4.1911        | 16.0  | 10992 | 4.0576          | 0.9601 | 0.9887 |
  | 4.1079        | 17.0  | 11679 | 4.0630          | 0.9544 | 0.9857 |
  | 4.1117        | 18.0  | 12366 | 4.0009          | 0.9558 | 0.9880 |
  | 4.0324        | 19.0  | 13053 | 3.9245          | 0.9540 | 0.9877 |
  | 3.9871        | 20.0  | 13740 | 3.9199          | 0.9540 | 0.9868 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  