readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - librispeech_asr
  metrics:
  - wer
  model-index:
  - name: whisper-ft-libri-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: 31.616341030195382
  ---
  
  <!-- 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-ft-libri-en
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the librispeech_asr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8069
  - Wer: 31.6163
  
  ## 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: 7.740176574997311e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 2
  - training_steps: 400
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 2.1717        | 0.38  | 5    | 2.1709          | 98.0462 |
  | 1.2371        | 0.77  | 10   | 1.2719          | 79.9290 |
  | 0.7577        | 1.15  | 15   | 1.0510          | 35.3464 |
  | 0.5325        | 1.54  | 20   | 0.9475          | 32.6821 |
  | 0.5545        | 1.92  | 25   | 0.8607          | 30.3730 |
  | 0.2957        | 2.31  | 30   | 0.8051          | 33.3925 |
  | 0.1846        | 2.69  | 35   | 0.7487          | 30.1954 |
  | 0.0748        | 3.08  | 40   | 0.6882          | 32.1492 |
  | 0.0709        | 3.46  | 45   | 0.6692          | 31.2611 |
  | 0.0908        | 3.85  | 50   | 0.6465          | 29.4849 |
  | 0.0764        | 4.23  | 55   | 0.6578          | 28.9520 |
  | 0.0259        | 4.62  | 60   | 0.6637          | 30.0178 |
  | 0.0178        | 5.0   | 65   | 0.6955          | 30.3730 |
  | 0.0131        | 5.38  | 70   | 0.6869          | 33.2149 |
  | 0.0162        | 5.77  | 75   | 0.7000          | 32.3268 |
  | 0.0081        | 6.15  | 80   | 0.6814          | 32.3268 |
  | 0.0075        | 6.54  | 85   | 0.6897          | 31.0835 |
  | 0.0069        | 6.92  | 90   | 0.7151          | 32.6821 |
  | 0.0062        | 7.31  | 95   | 0.7181          | 30.3730 |
  | 0.0056        | 7.69  | 100  | 0.7173          | 30.0178 |
  | 0.0052        | 8.08  | 105  | 0.7411          | 31.9716 |
  | 0.0073        | 8.46  | 110  | 0.7526          | 32.5044 |
  | 0.0061        | 8.85  | 115  | 0.7467          | 32.8597 |
  | 0.0034        | 9.23  | 120  | 0.7314          | 31.7940 |
  | 0.0122        | 9.62  | 125  | 0.7276          | 31.7940 |
  | 0.0429        | 10.0  | 130  | 0.7417          | 32.5044 |
  | 0.0032        | 10.38 | 135  | 0.7555          | 31.9716 |
  | 0.0141        | 10.77 | 140  | 0.7636          | 31.2611 |
  | 0.0038        | 11.15 | 145  | 0.7607          | 31.9716 |
  | 0.0038        | 11.54 | 150  | 0.7716          | 33.0373 |
  | 0.0035        | 11.92 | 155  | 0.7985          | 34.2806 |
  | 0.0038        | 12.31 | 160  | 0.7797          | 32.1492 |
  | 0.0036        | 12.69 | 165  | 0.7767          | 31.4387 |
  | 0.0022        | 13.08 | 170  | 0.7830          | 31.7940 |
  | 0.0033        | 13.46 | 175  | 0.7992          | 30.7282 |
  | 0.0019        | 13.85 | 180  | 0.7541          | 30.0178 |
  | 0.0016        | 14.23 | 185  | 0.7587          | 30.0178 |
  | 0.0027        | 14.62 | 190  | 0.7766          | 30.3730 |
  | 0.0016        | 15.0  | 195  | 0.8056          | 32.8597 |
  | 0.0015        | 15.38 | 200  | 0.8096          | 32.5044 |
  | 0.0012        | 15.77 | 205  | 0.7931          | 32.6821 |
  | 0.001         | 16.15 | 210  | 0.7829          | 31.6163 |
  | 0.0045        | 16.54 | 215  | 0.7774          | 30.9059 |
  | 0.0009        | 16.92 | 220  | 0.7750          | 30.1954 |
  | 0.0009        | 17.31 | 225  | 0.7780          | 28.9520 |
  | 0.0008        | 17.69 | 230  | 0.7803          | 29.1297 |
  | 0.0007        | 18.08 | 235  | 0.7807          | 29.6625 |
  | 0.0025        | 18.46 | 240  | 0.7813          | 30.1954 |
  | 0.0007        | 18.85 | 245  | 0.7840          | 30.0178 |
  | 0.0006        | 19.23 | 250  | 0.7860          | 30.0178 |
  | 0.0007        | 19.62 | 255  | 0.7839          | 30.1954 |
  | 0.0005        | 20.0  | 260  | 0.7834          | 30.1954 |
  | 0.0006        | 20.38 | 265  | 0.7844          | 30.3730 |
  | 0.0102        | 20.77 | 270  | 0.7859          | 30.7282 |
  | 0.0006        | 21.15 | 275  | 0.7901          | 30.7282 |
  | 0.0006        | 21.54 | 280  | 0.7950          | 30.7282 |
  | 0.0006    