readme: ---
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - automatic-speech-recognition
  - NbAiLab/NST
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-NST-cons2e5
    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. -->
  
  # whisper-NST-cons2e5
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NBAILAB/NST - NO-CLOSE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3521
  - Wer: 11.8586
  
  ## 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: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant_with_warmup
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2517        | 0.1   | 1000  | 0.4131          | 18.4721 |
  | 0.1931        | 0.2   | 2000  | 0.3531          | 19.0422 |
  | 0.1598        | 0.3   | 3000  | 0.3605          | 16.8757 |
  | 0.1541        | 0.4   | 4000  | 0.3367          | 14.4812 |
  | 0.1443        | 0.5   | 5000  | 0.3274          | 13.3409 |
  | 0.1301        | 0.6   | 6000  | 0.3481          | 10.7184 |
  | 0.1266        | 0.7   | 7000  | 0.3452          | 12.9989 |
  | 0.1216        | 0.8   | 8000  | 0.3215          | 10.8324 |
  | 0.1121        | 0.9   | 9000  | 0.3160          | 11.5165 |
  | 0.1171        | 1.0   | 10000 | 0.3521          | 11.8586 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  