readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: nick_asr_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_v2
  
  This model is a fine-tuned version of [ntoldalagi/nick_asr_v2](https://huggingface.co/ntoldalagi/nick_asr_v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4562
  - Wer: 0.6422
  - Cer: 0.2409
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Cer    | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
  | 0.2616        | 0.44  | 300   | 0.2905 | 1.2200          | 0.7496 |
  | 0.441         | 0.87  | 600   | 0.2866 | 1.1936          | 0.7385 |
  | 0.4366        | 1.31  | 900   | 0.2795 | 1.1584          | 0.7274 |
  | 0.3982        | 1.75  | 1200  | 0.2808 | 1.2033          | 0.7274 |
  | 0.3891        | 2.18  | 1500  | 0.2753 | 1.2044          | 0.7166 |
  | 0.3508        | 2.91  | 2000  | 1.2382 | 0.7220          | 0.2743 |
  | 0.2783        | 4.37  | 3000  | 1.3327 | 0.7177          | 0.2705 |
  | 0.2495        | 5.82  | 4000  | 1.2286 | 0.6749          | 0.2638 |
  | 0.1982        | 7.28  | 5000  | 1.3073 | 0.6721          | 0.2585 |
  | 0.1717        | 8.73  | 6000  | 1.2941 | 0.6627          | 0.2500 |
  | 0.1508        | 10.19 | 7000  | 1.3625 | 0.6584          | 0.2490 |
  | 0.1329        | 11.64 | 8000  | 1.3863 | 0.6584          | 0.2474 |
  | 0.1303        | 13.1  | 9000  | 1.3714 | 0.6534          | 0.2449 |
  | 0.1159        | 14.56 | 10000 | 1.4043 | 0.6473          | 0.2442 |
  | 0.1015        | 16.01 | 11000 | 1.4245 | 0.6498          | 0.2419 |
  | 0.098         | 17.47 | 12000 | 1.4410 | 0.6440          | 0.2425 |
  | 0.0869        | 18.92 | 13000 | 1.4562 | 0.6422          | 0.2409 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.12.1
  