readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - librispeech_asr
  metrics:
  - wer
  model-index:
  - name: whisper-small-en
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: librispeech_asr
        type: librispeech_asr
        config: clean
        split: test
        args: clean
      metrics:
      - name: Wer
        type: wer
        value: 124.51154529307283
  ---
  
  <!-- 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-en
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the librispeech_asr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 6.7832
  - Wer: 124.5115
  
  ## 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
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2
  - training_steps: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer       |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|
  | 9.6259        | 1.57  | 5    | 10.7408         | 1127.3535 |
  | 11.5288       | 3.29  | 10   | 9.2534          | 100.0     |
  | 10.9249       | 4.86  | 15   | 7.8357          | 100.0     |
  | 7.0442        | 6.57  | 20   | 6.9971          | 595.3819  |
  | 8.6762        | 8.29  | 25   | 5.6135          | 312.2558  |
  | 5.4239        | 9.86  | 30   | 5.4885          | 97.1581   |
  | 4.986         | 11.57 | 35   | 5.2888          | 628.7744  |
  | 6.708         | 13.29 | 40   | 4.9665          | 277.6199  |
  | 3.9096        | 14.86 | 45   | 5.0861          | 631.9716  |
  | 3.2326        | 16.57 | 50   | 5.0090          | 279.7513  |
  | 3.9691        | 18.29 | 55   | 5.0804          | 133.2149  |
  | 1.8661        | 19.86 | 60   | 5.4423          | 317.5844  |
  | 1.1588        | 21.57 | 65   | 5.7955          | 119.5382  |
  | 1.0355        | 23.29 | 70   | 6.0458          | 190.2309  |
  | 0.3455        | 24.86 | 75   | 6.3057          | 106.7496  |
  | 0.142         | 26.57 | 80   | 6.5767          | 209.9467  |
  | 0.1722        | 28.29 | 85   | 6.5937          | 101.4210  |
  | 0.0816        | 29.86 | 90   | 6.7679          | 149.7336  |
  | 0.079         | 31.57 | 95   | 6.8008          | 133.5702  |
  | 0.1007        | 33.29 | 100  | 6.7832          | 124.5115  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  