---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 16.318103103769815
---

<!-- 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. -->

# openai/whisper-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2860
- Wer: 16.3181
- Cer: 4.1450

## 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: 8
- 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: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
| 0.1563        | 1.0   | 2500  | 0.2524          | 19.8570 | 5.1738 |
| 0.032         | 2.01  | 5000  | 0.2567          | 18.5627 | 4.7793 |
| 0.013         | 3.01  | 7500  | 0.2637          | 17.7723 | 4.6664 |
| 0.0057        | 4.02  | 10000 | 0.2703          | 17.0596 | 4.3662 |
| 0.0012        | 5.02  | 12500 | 0.2696          | 17.8322 | 5.2286 |
| 0.003         | 6.03  | 15000 | 0.2800          | 16.7200 | 4.2972 |
| 0.0003        | 7.03  | 17500 | 0.2834          | 16.4091 | 4.2018 |
| 0.0002        | 8.04  | 20000 | 0.2860          | 16.3181 | 4.1450 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2