---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: openai/whisper-base-Ko
  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: 6.550218340611353
---

<!-- 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. -->

# openai/whisper-base-Ko

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the kresnik/zeroth_korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0970
- Wer: 6.5502
- Cer: 2.9012

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.3775        | 0.72  | 500  | 0.2690          | 22.8580 | 8.2443 |
| 0.1316        | 1.44  | 1000 | 0.1760          | 15.9012 | 6.8624 |
| 0.0658        | 2.16  | 1500 | 0.1285          | 10.6761 | 4.2753 |
| 0.0273        | 2.87  | 2000 | 0.1133          | 10.6309 | 5.0251 |
| 0.0112        | 3.59  | 2500 | 0.1040          | 8.0560  | 3.3448 |
| 0.0055        | 4.31  | 3000 | 0.1010          | 7.3633  | 3.2389 |
| 0.0024        | 5.03  | 3500 | 0.0979          | 6.6105  | 2.9837 |
| 0.0013        | 5.75  | 4000 | 0.0967          | 6.7309  | 2.9680 |
| 0.0009        | 6.47  | 4500 | 0.0967          | 6.6707  | 2.9405 |
| 0.0008        | 7.18  | 5000 | 0.0970          | 6.5502  | 2.9012 |


### Framework versions

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