---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
- whisper-event
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: Whisper Small Korean
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Zeroth Korean
      type: kresnik/zeroth_korean
      config: clean
      split: test
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 6.761029965366662
---

<!-- 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 Korean

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Zeroth Korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0899
- Wer: 6.7610

## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1277        | 0.72  | 1000 | 0.1489          | 12.2271 |
| 0.0379        | 1.44  | 2000 | 0.1053          | 6.7159  |
| 0.0138        | 2.16  | 3000 | 0.0918          | 6.0382  |
| 0.0141        | 2.87  | 4000 | 0.0899          | 6.7610  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0a0+d0d6b1f
- Datasets 2.7.1
- Tokenizers 0.13.2