---
library_name: transformers
language:
- ko
license: mit
base_model: imTak/whisper_large_v3_turbo_Korean2
tags:
- generated_from_trainer
datasets:
- imTak/korean-speak-Develop
metrics:
- wer
model-index:
- name: Whisper large v3 turbo Korean-Develop
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Develop
      type: imTak/korean-speak-Develop
      args: 'config: ko, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 16.43703941044537
---

<!-- 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 large v3 turbo Korean-Develop

This model is a fine-tuned version of [imTak/whisper_large_v3_ko_ft_ft](https://huggingface.co/imTak/whisper_large_v3_ko_ft_ft) on the Develop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3054
- Wer: 16.4370

## 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: 32
- 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2119        | 1.9455  | 500  | 0.2721          | 22.6690 |
| 0.0714        | 3.8911  | 1000 | 0.2542          | 19.9135 |
| 0.0145        | 5.8366  | 1500 | 0.2417          | 18.5037 |
| 0.0018        | 7.7821  | 2000 | 0.2410          | 16.6453 |
| 0.0263        | 9.7276  | 2500 | 0.2818          | 19.4169 |
| 0.0179        | 11.6732 | 3000 | 0.2806          | 18.5838 |
| 0.008         | 13.6187 | 3500 | 0.2977          | 18.1032 |
| 0.0072        | 15.5642 | 4000 | 0.2920          | 17.8949 |
| 0.0011        | 17.5097 | 4500 | 0.2875          | 16.8376 |
| 0.0024        | 19.4553 | 5000 | 0.3072          | 17.8629 |
| 0.0009        | 21.4008 | 5500 | 0.2943          | 16.8536 |
| 0.0002        | 23.3463 | 6000 | 0.3041          | 16.8055 |
| 0.0001        | 25.2918 | 6500 | 0.2993          | 16.6773 |
| 0.0001        | 27.2374 | 7000 | 0.3016          | 16.4851 |
| 0.0001        | 29.1829 | 7500 | 0.3043          | 16.4050 |
| 0.0001        | 31.1284 | 8000 | 0.3054          | 16.4370 |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3