---
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: Whisper Small Ko - haseong8012
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: kresnik/zeroth_korean
      type: kresnik/zeroth_korean
      config: clean
      split: test
      args: 'config: ko, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 6.776087938563469
---

<!-- 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 - haseong8012

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the kresnik/zeroth_korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0981
- Wer: 6.7761
- Cer: 2.8934

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.0873        | 1.44  | 1000 | 0.1706          | 15.1333 | 6.0733 |
| 0.0274        | 2.87  | 2000 | 0.1186          | 9.6220  | 3.9887 |
| 0.0034        | 4.31  | 3000 | 0.1050          | 7.7699  | 3.1878 |
| 0.0011        | 5.75  | 4000 | 0.0990          | 7.4838  | 3.6079 |
| 0.0008        | 7.18  | 5000 | 0.0981          | 6.7761  | 2.8934 |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.13.3