readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: nick_asr_COMBO_v2
    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_v2
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4474
  - Wer: 0.6535
  - Cer: 0.2486
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
  | 0.3049        | 1.0   | 687  | 1.5013          | 0.7015 | 0.2607 |
  | 0.2294        | 2.0   | 1374 | 1.5933          | 0.6693 | 0.2612 |
  | 0.261         | 3.0   | 2061 | 1.6275          | 0.6985 | 0.2687 |
  | 0.2658        | 4.0   | 2748 | 1.5568          | 0.6729 | 0.2581 |
  | 0.1704        | 5.0   | 3435 | 1.5363          | 0.6650 | 0.2529 |
  | 0.2537        | 6.0   | 4122 | 1.5764          | 0.6669 | 0.2542 |
  | 0.2333        | 7.0   | 4809 | 1.5285          | 0.6596 | 0.2519 |
  | 0.168         | 8.0   | 5496 | 1.4945          | 0.6571 | 0.2500 |
  | 0.3263        | 9.0   | 6183 | 1.4968          | 0.6547 | 0.2510 |
  | 0.3238        | 10.0  | 6870 | 1.4474          | 0.6535 | 0.2486 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  