readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-small-sp
    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-small-sp
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4485
  - Wer: 20.6842
  
  ## 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: 0.0005
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 25000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 2.2671        | 0.13  | 1000  | 2.2108          | 76.2667 |
  | 1.4465        | 0.26  | 2000  | 1.6057          | 67.8753 |
  | 1.0997        | 0.39  | 3000  | 1.1928          | 54.2433 |
  | 0.9389        | 0.52  | 4000  | 1.0020          | 47.8307 |
  | 0.7881        | 0.65  | 5000  | 0.8933          | 46.0046 |
  | 0.7596        | 0.78  | 6000  | 0.7721          | 38.5595 |
  | 0.5678        | 0.91  | 7000  | 0.6903          | 36.2897 |
  | 0.4412        | 1.04  | 8000  | 0.6476          | 32.7473 |
  | 0.4239        | 1.17  | 9000  | 0.5973          | 30.8142 |
  | 0.3935        | 1.3   | 10000 | 0.5444          | 29.0208 |
  | 0.3307        | 1.43  | 11000 | 0.5024          | 27.0434 |
  | 0.2937        | 1.56  | 12000 | 0.4608          | 24.7318 |
  | 0.2471        | 1.69  | 13000 | 0.4259          | 22.8940 |
  | 0.2357        | 1.82  | 14000 | 0.3936          | 21.6018 |
  | 0.2292        | 1.95  | 15000 | 0.3776          | 20.8004 |
  | 0.1493        | 2.08  | 16000 | 0.4599          | 24.0491 |
  | 0.1708        | 2.21  | 17000 | 0.4370          | 23.3443 |
  | 0.1385        | 2.34  | 18000 | 0.4277          | 22.3171 |
  | 0.1288        | 2.47  | 19000 | 0.4050          | 21.0118 |
  | 0.1627        | 2.6   | 20000 | 0.4507          | 23.4004 |
  | 0.1675        | 2.73  | 21000 | 0.4346          | 22.8261 |
  | 0.159         | 2.86  | 22000 | 0.4179          | 22.2949 |
  | 0.1458        | 2.99  | 23000 | 0.3978          | 21.0810 |
  | 0.0487        | 3.12  | 24000 | 0.4456          | 20.8617 |
  | 0.0401        | 3.25  | 25000 | 0.4485          | 20.6842 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  