---
library_name: transformers
language:
- ko
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small ko
  results: []
---

<!-- 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-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the custom dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1905
- Wer: 12.1097

## 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: 4e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.689         | 0.0107 | 10   | 1.0086          | 45.3169  |
| 0.0756        | 0.0214 | 20   | 0.6343          | 38.0322  |
| 0.0145        | 0.0322 | 30   | 0.6367          | 41.3434  |
| 0.0212        | 0.0429 | 40   | 0.7120          | 42.6679  |
| 0.0205        | 0.0536 | 50   | 0.4694          | 32.6395  |
| 0.016         | 0.0643 | 60   | 0.5533          | 38.7890  |
| 0.014         | 0.0750 | 70   | 0.4716          | 30.8420  |
| 0.0115        | 0.0857 | 80   | 0.6191          | 30.9366  |
| 0.0228        | 0.0965 | 90   | 0.7998          | 43.8978  |
| 0.0191        | 0.1072 | 100  | 0.7273          | 36.4238  |
| 0.026         | 0.1179 | 110  | 0.7720          | 42.3841  |
| 0.0196        | 0.1286 | 120  | 0.9171          | 79.4702  |
| 0.0178        | 0.1393 | 130  | 1.1460          | 136.0454 |
| 0.037         | 0.1501 | 140  | 0.5558          | 62.8193  |
| 0.0237        | 0.1608 | 150  | 0.6369          | 109.6500 |
| 0.0195        | 0.1715 | 160  | 0.6671          | 38.7890  |
| 0.0151        | 0.1822 | 170  | 0.6717          | 53.9262  |
| 0.0479        | 0.1929 | 180  | 0.5412          | 68.1173  |
| 0.0187        | 0.2036 | 190  | 0.5311          | 60.2649  |
| 0.0191        | 0.2144 | 200  | 0.4761          | 33.3964  |
| 0.0149        | 0.2251 | 210  | 0.6630          | 38.5998  |
| 0.0285        | 0.2358 | 220  | 0.6162          | 36.8023  |
| 0.0134        | 0.2465 | 230  | 0.5166          | 31.5043  |
| 0.0143        | 0.2572 | 240  | 0.6748          | 55.3453  |
| 0.0185        | 0.2680 | 250  | 0.5091          | 28.1930  |
| 0.0106        | 0.2787 | 260  | 0.4697          | 28.0984  |
| 0.0163        | 0.2894 | 270  | 0.4483          | 24.4087  |
| 0.0186        | 0.3001 | 280  | 0.3112          | 22.1381  |
| 0.018         | 0.3108 | 290  | 0.3752          | 26.7739  |
| 0.0067        | 0.3215 | 300  | 0.5734          | 28.0984  |
| 0.0129        | 0.3323 | 310  | 0.3768          | 22.3273  |
| 0.0196        | 0.3430 | 320  | 0.3069          | 23.4626  |
| 0.0096        | 0.3537 | 330  | 0.3197          | 20.5298  |
| 0.0143        | 0.3644 | 340  | 0.3839          | 43.8032  |
| 0.0082        | 0.3751 | 350  | 0.3098          | 80.1325  |
| 0.0099        | 0.3859 | 360  | 0.2946          | 77.6727  |
| 0.0146        | 0.3966 | 370  | 0.3007          | 19.3945  |
| 0.0115        | 0.4073 | 380  | 0.2685          | 17.3132  |
| 0.0058        | 0.4180 | 390  | 0.2686          | 16.7455  |
| 0.0067        | 0.4287 | 400  | 0.2572          | 15.6102  |
| 0.0095        | 0.4394 | 410  | 0.2400          | 14.9480  |
| 0.0085        | 0.4502 | 420  | 0.2436          | 15.2318  |
| 0.005         | 0.4609 | 430  | 0.2426          | 15.0426  |
| 0.0044        | 0.4716 | 440  | 0.2318          | 13.8127  |
| 0.0063        | 0.4823 | 450  | 0.2262          | 12.7720  |
| 0.0093        | 0.4930 | 460  | 0.2098          | 12.1097  |
| 0.0054        | 0.5038 | 470  | 0.2042          | 12.2990  |
| 0.0046        | 0.5145 | 480  | 0.1941          | 11.9205  |
| 0.0071        | 0.5252 | 490  | 0.1913          | 12.1097  |
| 0.0066        | 0.5359 | 500  | 0.1905          | 12.1097  |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0