readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: nick_asr_COMBO
    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. -->
  
  # nick_asr_COMBO
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4313
  - Wer: 0.6723
  - Cer: 0.2408
  
  ## 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: 5e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 0.0857        | 1.0   | 687  | 1.3883          | 0.7082 | 0.2576 |
  | 0.0627        | 2.0   | 1374 | 1.4099          | 0.7076 | 0.2561 |
  | 0.0697        | 3.0   | 2061 | 1.3864          | 0.6906 | 0.2486 |
  | 0.0575        | 4.0   | 2748 | 1.4356          | 0.6906 | 0.2455 |
  | 0.0552        | 5.0   | 3435 | 1.4061          | 0.6778 | 0.2440 |
  | 0.0631        | 6.0   | 4122 | 1.4541          | 0.6839 | 0.2444 |
  | 0.0418        | 7.0   | 4809 | 1.4258          | 0.6930 | 0.2465 |
  | 0.0407        | 8.0   | 5496 | 1.4193          | 0.6809 | 0.2451 |
  | 0.0487        | 9.0   | 6183 | 1.4261          | 0.6778 | 0.2424 |
  | 0.0371        | 10.0  | 6870 | 1.4313          | 0.6723 | 0.2408 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  