---
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Korean
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs ko_kr
      type: google/fleurs
      config: ko_kr
      split: test
      args: ko_kr
    metrics:
    - name: Wer
      type: wer
      value: 27.43440746610319
---

<!-- 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 Base Korean

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs ko_kr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4901
- Wer: 27.4344

## 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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3225        | 66.0  | 500  | 0.5002          | 27.9275 |
| 0.1185        | 133.0 | 1000 | 0.4901          | 27.4344 |
| 0.0468        | 199.0 | 1500 | 0.5047          | 27.4696 |
| 0.0268        | 266.0 | 2000 | 0.5147          | 27.8746 |
| 0.0189        | 333.0 | 2500 | 0.5218          | 28.0507 |
| 0.0145        | 399.0 | 3000 | 0.5273          | 28.4733 |
| 0.0121        | 466.0 | 3500 | 0.5318          | 28.6318 |
| 0.0107        | 533.0 | 4000 | 0.5352          | 28.6846 |
| 0.0098        | 599.0 | 4500 | 0.5376          | 28.8079 |
| 0.0095        | 666.0 | 5000 | 0.5385          | 28.8079 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0