---
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- gglabs/stt-test-1223
metrics:
- wer
model-index:
- name: Whisper Small ko
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: custom
      type: gglabs/stt-test-1223
      args: 'config: ko, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 46.19565217391305
---

<!-- 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 custom dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0537
- Wer: 46.1957

## 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: 8
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.9628        | 0.0112 | 10   | 1.5113          | 55.4348 |
| 1.0128        | 0.0223 | 20   | 1.5033          | 53.2609 |
| 0.7642        | 0.0335 | 30   | 1.4807          | 48.3696 |
| 0.683         | 0.0446 | 40   | 1.4422          | 47.8261 |
| 0.4836        | 0.0558 | 50   | 1.3840          | 48.3696 |
| 0.207         | 0.0670 | 60   | 1.2772          | 49.4565 |
| 0.0984        | 0.0781 | 70   | 1.1608          | 47.8261 |
| 0.1485        | 0.0893 | 80   | 1.1003          | 45.1087 |
| 0.0538        | 0.1004 | 90   | 1.0760          | 44.5652 |
| 0.0349        | 0.1116 | 100  | 1.0537          | 46.1957 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1