---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-dv
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: dv
      split: test
      args: dv
    metrics:
    - name: Wer
      type: wer
      value: 11.072086796258302
---

<!-- 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-dv

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2738
- Wer Ortho: 56.8842
- Wer: 11.0721

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.1237        | 1.63  | 500  | 0.1702          | 63.0963   | 13.1429 |
| 0.0494        | 3.26  | 1000 | 0.1662          | 57.8592   | 11.6285 |
| 0.0315        | 4.89  | 1500 | 0.1894          | 58.3397   | 11.3937 |
| 0.0121        | 6.51  | 2000 | 0.2257          | 57.7756   | 11.5502 |
| 0.005         | 8.14  | 2500 | 0.2643          | 56.9747   | 11.1573 |
| 0.0056        | 9.77  | 3000 | 0.2738          | 56.8842   | 11.0721 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3