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---
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 |