---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-large
datasets:
- Marcusxx/gwanju
metrics:
- wer
model-index:
- name: gwanju_largeWER_model
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Marcusxx/gwanju
      type: Marcusxx/gwanju
      args: 'config: ko, split: valid'
    metrics:
    - type: wer
      value: 41.85458286890166
      name: Wer
---

<!-- 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. -->

# gwanju_largeWER_model

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Marcusxx/gwanju dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3334
- Wer: 41.8546

## 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: 100
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4683        | 0.0741 | 250  | 0.4884          | 104.4328 |
| 0.4578        | 0.1482 | 500  | 0.4522          | 55.8304  |
| 0.4675        | 0.2223 | 750  | 0.4379          | 65.3948  |
| 0.4338        | 0.2964 | 1000 | 0.4225          | 65.4206  |
| 0.4547        | 0.3705 | 1250 | 0.4023          | 63.5814  |
| 0.3676        | 0.4446 | 1500 | 0.3914          | 47.9551  |
| 0.3752        | 0.5187 | 1750 | 0.3840          | 48.3838  |
| 0.3584        | 0.5928 | 2000 | 0.3745          | 44.8641  |
| 0.4221        | 0.6669 | 2250 | 0.3638          | 42.4548  |
| 0.3432        | 0.7410 | 2500 | 0.3563          | 42.7206  |
| 0.3993        | 0.8151 | 2750 | 0.3497          | 44.7955  |
| 0.3448        | 0.8892 | 3000 | 0.3437          | 43.3722  |
| 0.3441        | 0.9632 | 3250 | 0.3381          | 40.4270  |
| 0.2317        | 1.0373 | 3500 | 0.3350          | 39.5782  |
| 0.2063        | 1.1114 | 3750 | 0.3339          | 40.8385  |
| 0.2016        | 1.1855 | 4000 | 0.3334          | 41.8546  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1