---
library_name: peft
language:
- ko
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
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: 0.1812

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 256
- 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8642        | 0.1449 | 10   | 1.5475          |
| 0.8061        | 0.2899 | 20   | 1.4627          |
| 0.6409        | 0.4348 | 30   | 1.2193          |
| 0.3296        | 0.5797 | 40   | 0.8200          |
| 0.178         | 0.7246 | 50   | 0.7032          |
| 0.1336        | 0.8696 | 60   | 0.6138          |
| 0.1064        | 1.0145 | 70   | 0.5193          |
| 0.0846        | 1.1594 | 80   | 0.4691          |
| 0.0728        | 1.3043 | 90   | 0.4360          |
| 0.0681        | 1.4493 | 100  | 0.4071          |
| 0.0566        | 1.5942 | 110  | 0.3891          |
| 0.0613        | 1.7391 | 120  | 0.3695          |
| 0.0441        | 1.8841 | 130  | 0.3587          |
| 0.0469        | 2.0290 | 140  | 0.3461          |
| 0.0426        | 2.1739 | 150  | 0.3373          |
| 0.0383        | 2.3188 | 160  | 0.3249          |
| 0.037         | 2.4638 | 170  | 0.3150          |
| 0.0516        | 2.6087 | 180  | 0.2967          |
| 0.0403        | 2.7536 | 190  | 0.2888          |
| 0.045         | 2.8986 | 200  | 0.2782          |
| 0.0365        | 3.0435 | 210  | 0.2668          |
| 0.0309        | 3.1884 | 220  | 0.2598          |
| 0.0341        | 3.3333 | 230  | 0.2542          |
| 0.0289        | 3.4783 | 240  | 0.2487          |
| 0.0364        | 3.6232 | 250  | 0.2417          |
| 0.0353        | 3.7681 | 260  | 0.2372          |
| 0.0312        | 3.9130 | 270  | 0.2293          |
| 0.0317        | 4.0580 | 280  | 0.2263          |
| 0.029         | 4.2029 | 290  | 0.2254          |
| 0.0348        | 4.3478 | 300  | 0.2168          |
| 0.0299        | 4.4928 | 310  | 0.2101          |
| 0.0327        | 4.6377 | 320  | 0.2085          |
| 0.0252        | 4.7826 | 330  | 0.2071          |
| 0.0246        | 4.9275 | 340  | 0.2020          |
| 0.0219        | 5.0725 | 350  | 0.1990          |
| 0.0234        | 5.2174 | 360  | 0.1997          |
| 0.0269        | 5.3623 | 370  | 0.1969          |
| 0.0262        | 5.5072 | 380  | 0.1961          |
| 0.0293        | 5.6522 | 390  | 0.1920          |
| 0.0247        | 5.7971 | 400  | 0.1891          |
| 0.0273        | 5.9420 | 410  | 0.1869          |
| 0.0205        | 6.0870 | 420  | 0.1866          |
| 0.0168        | 6.2319 | 430  | 0.1860          |
| 0.0261        | 6.3768 | 440  | 0.1851          |
| 0.0254        | 6.5217 | 450  | 0.1839          |
| 0.0258        | 6.6667 | 460  | 0.1830          |
| 0.0242        | 6.8116 | 470  | 0.1825          |
| 0.0259        | 6.9565 | 480  | 0.1818          |
| 0.0234        | 7.1014 | 490  | 0.1813          |
| 0.0194        | 7.2464 | 500  | 0.1812          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0