---
language:
- ko
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Marcusxx/gwanju4
model-index:
- name: gwanju4_test__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. -->

# gwanju4_test__model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Marcusxx/gwanju4 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5722
- Cer: 275.0

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer   |
|:-------------:|:------:|:----:|:---------------:|:-----:|
| 1.9955        | 50.0   | 50   | 4.8936          | 425.0 |
| 0.3976        | 100.0  | 100  | 2.6194          | 275.0 |
| 0.0001        | 150.0  | 150  | 2.5074          | 275.0 |
| 0.0           | 200.0  | 200  | 2.4715          | 325.0 |
| 0.0           | 250.0  | 250  | 2.4384          | 325.0 |
| 0.0           | 300.0  | 300  | 2.3972          | 275.0 |
| 0.0           | 350.0  | 350  | 2.3937          | 275.0 |
| 0.0           | 400.0  | 400  | 2.4084          | 275.0 |
| 0.0           | 450.0  | 450  | 2.4310          | 275.0 |
| 0.0           | 500.0  | 500  | 2.4561          | 275.0 |
| 0.0           | 550.0  | 550  | 2.4782          | 275.0 |
| 0.0           | 600.0  | 600  | 2.5006          | 275.0 |
| 0.0           | 650.0  | 650  | 2.5150          | 275.0 |
| 0.0           | 700.0  | 700  | 2.5310          | 275.0 |
| 0.0           | 750.0  | 750  | 2.5415          | 275.0 |
| 0.0           | 800.0  | 800  | 2.5517          | 275.0 |
| 0.0           | 850.0  | 850  | 2.5592          | 275.0 |
| 0.0           | 900.0  | 900  | 2.5674          | 275.0 |
| 0.0           | 950.0  | 950  | 2.5723          | 275.0 |
| 0.0           | 1000.0 | 1000 | 2.5722          | 275.0 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1