---
language:
- ko
license: apache-2.0
base_model: openai/whisper-large
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Marcusxx/gwanju
model-index:
- name: gwanju_large_model
  results: []
---

<!-- 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_large_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: 0.3547
- Cer: 395.4097

## 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: 250
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Cer      |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.4409        | 0.2964 | 1000  | 0.4335          | 106.5804 |
| 0.3824        | 0.5928 | 2000  | 0.3930          | 442.5527 |
| 0.3757        | 0.8892 | 3000  | 0.3727          | 455.4447 |
| 0.2271        | 1.1855 | 4000  | 0.3712          | 463.1818 |
| 0.2528        | 1.4819 | 5000  | 0.3600          | 468.4532 |
| 0.2068        | 1.7783 | 6000  | 0.3523          | 468.7220 |
| 0.1221        | 2.0747 | 7000  | 0.3592          | 480.3038 |
| 0.1157        | 2.3711 | 8000  | 0.3614          | 377.9116 |
| 0.121         | 2.6675 | 9000  | 0.3579          | 401.4220 |
| 0.1046        | 2.9638 | 10000 | 0.3547          | 395.4097 |


### Framework versions

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