readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-NST2-unfreeze-constanti-low-lr
    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-NST2-unfreeze-constanti-low-lr
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3562
  - Wer: 8.5519
  
  ## 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: 1e-05
  - train_batch_size: 96
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - training_steps: 20000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1901        | 0.05  | 1000  | 0.3069          | 14.8233 |
  | 0.1323        | 0.1   | 2000  | 0.2687          | 11.2885 |
  | 0.1137        | 0.15  | 3000  | 0.2620          | 10.8324 |
  | 0.1022        | 0.2   | 4000  | 0.2976          | 9.0080  |
  | 0.0937        | 0.25  | 5000  | 0.2584          | 9.5781  |
  | 0.0875        | 0.3   | 6000  | 0.2704          | 20.2965 |
  | 0.0592        | 1.05  | 7000  | 0.2751          | 9.0080  |
  | 0.0488        | 1.1   | 8000  | 0.2778          | 8.6659  |
  | 0.0475        | 1.15  | 9000  | 0.2792          | 9.4641  |
  | 0.0439        | 1.2   | 10000 | 0.2880          | 8.3238  |
  | 0.0425        | 1.25  | 11000 | 0.2954          | 8.5519  |
  | 0.0416        | 1.3   | 12000 | 0.2896          | 20.2965 |
  | 0.0289        | 2.05  | 13000 | 0.2990          | 7.9818  |
  | 0.0229        | 2.1   | 14000 | 0.3027          | 7.4116  |
  | 0.0248        | 2.15  | 15000 | 0.2968          | 8.6659  |
  | 0.0225        | 2.2   | 16000 | 0.3100          | 8.5519  |
  | 0.0222        | 2.25  | 17000 | 0.3132          | 9.3501  |
  | 0.0219        | 2.3   | 18000 | 0.3230          | 7.6397  |
  | 0.0162        | 3.04  | 19000 | 0.3380          | 9.8062  |
  | 0.0132        | 3.09  | 20000 | 0.3562          | 8.5519  |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  