---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- Marcusxx/gwanju
model-index:
- name: gwanju_medium2_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_medium2_model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Marcusxx/gwanju dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3592
- Cer: 44.1724

## 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      |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.4478        | 0.2964 | 1000  | 0.4342          | 48.5130  |
| 0.3965        | 0.5928 | 2000  | 0.3973          | 401.9235 |
| 0.3913        | 0.8892 | 3000  | 0.3777          | 23.1253  |
| 0.236         | 1.1855 | 4000  | 0.3685          | 27.0142  |
| 0.2617        | 1.4819 | 5000  | 0.3638          | 31.4542  |
| 0.2245        | 1.7783 | 6000  | 0.3556          | 24.0368  |
| 0.1363        | 2.0747 | 7000  | 0.3582          | 27.9426  |
| 0.1232        | 2.3711 | 8000  | 0.3629          | 29.3680  |
| 0.1299        | 2.6675 | 9000  | 0.3615          | 40.2485  |
| 0.1191        | 2.9638 | 10000 | 0.3592          | 44.1724  |


### Framework versions

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