---
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        | 21.92 | 285  | 0.7975          | 31.0835 |
| 0.0006        | 22.31 | 290  | 0.7984          | 30.7282 |
| 0.0006        | 22.69 | 295  | 0.7954          | 30.3730 |
| 0.0005        | 23.08 | 300  | 0.7935          | 31.0835 |
| 0.0005        | 23.46 | 305  | 0.7928          | 31.0835 |
| 0.0005        | 23.85 | 310  | 0.7933          | 31.2611 |
| 0.0038        | 24.23 | 315  | 0.7950          | 30.9059 |
| 0.0005        | 24.62 | 320  | 0.7976          | 31.6163 |
| 0.0004        | 25.0  | 325  | 0.7995          | 31.7940 |
| 0.0004        | 25.38 | 330  | 0.8006          | 31.4387 |
| 0.0004        | 25.77 | 335  | 0.8005          | 31.6163 |
| 0.0005        | 26.15 | 340  | 0.8011          | 31.4387 |
| 0.0004        | 26.54 | 345  | 0.8020          | 31.6163 |
| 0.0004        | 26.92 | 350  | 0.8024          | 31.4387 |
| 0.0017        | 27.31 | 355  | 0.8029          | 31.4387 |
| 0.0004        | 27.69 | 360  | 0.8035          | 31.4387 |
| 0.0004        | 28.08 | 365  | 0.8045          | 31.4387 |
| 0.0004        | 28.46 | 370  | 0.8049          | 31.4387 |
| 0.0004        | 28.85 | 375  | 0.8056          | 31.4387 |
| 0.0011        | 29.23 | 380  | 0.8060          | 31.4387 |
| 0.0004        | 29.62 | 385  | 0.8065          | 31.4387 |
| 0.0004        | 30.0  | 390  | 0.8065          | 31.4387 |
| 0.0004        | 30.38 | 395  | 0.8068          | 31.4387 |
| 0.0004        | 30.77 | 400  | 0.8069          | 31.6163 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2