---
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- GGarri/customdataset
metrics:
- wer
model-index:
- name: Whisper Small ko
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: customdata
      type: GGarri/customdataset
    metrics:
    - name: Wer
      type: wer
      value: 6.9309637730690365
---

<!-- 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 ko

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the customdata dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0268
- Cer: 6.5045
- Wer: 6.9310

## 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: 32
- 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 3.6391        | 0.54  | 25   | 3.3230          | 83.6552 | 35.4340 |
| 2.7648        | 1.09  | 50   | 2.3011          | 81.2725 | 31.6473 |
| 1.8272        | 1.63  | 75   | 1.4490          | 85.9460 | 43.8688 |
| 1.0827        | 2.17  | 100  | 0.8137          | 72.8033 | 59.1524 |
| 0.6201        | 2.72  | 125  | 0.4756          | 50.5476 | 49.9522 |
| 0.3539        | 3.26  | 150  | 0.3005          | 31.1094 | 31.5926 |
| 0.2358        | 3.8   | 175  | 0.1969          | 29.5962 | 31.3192 |
| 0.1501        | 4.35  | 200  | 0.1352          | 21.1688 | 21.7772 |
| 0.0967        | 4.89  | 225  | 0.0846          | 18.6941 | 19.0431 |
| 0.0471        | 5.43  | 250  | 0.0350          | 18.3931 | 18.9200 |
| 0.0162        | 5.98  | 275  | 0.0335          | 18.9616 | 19.5215 |
| 0.0121        | 6.52  | 300  | 0.0324          | 14.1293 | 15.5707 |
| 0.011         | 7.07  | 325  | 0.0261          | 12.9755 | 14.3267 |
| 0.0078        | 7.61  | 350  | 0.0223          | 9.3220  | 10.5400 |
| 0.0075        | 8.15  | 375  | 0.0217          | 5.8106  | 6.5482  |
| 0.0052        | 8.7   | 400  | 0.0208          | 7.9926  | 8.6945  |
| 0.0048        | 9.24  | 425  | 0.0213          | 5.3424  | 5.7280  |
| 0.0053        | 9.78  | 450  | 0.0212          | 7.5328  | 7.9973  |
| 0.004         | 10.33 | 475  | 0.0213          | 5.7186  | 5.9740  |
| 0.0054        | 10.87 | 500  | 0.0268          | 6.5045  | 6.9310  |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2