---
language:
- ko
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: openai/whisper-large-v2
datasets:
- customd_ataset
model-index:
- name: Whisper large-v2 Korean - ML_project_custom_data_3epoch_with500_ko
  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. -->

# Whisper large-v2 Korean - ML_project_custom_data_3epoch_with500_ko

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the customd_ataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6315
- Cer: 102.3375

## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3587        | 1.0   | 113  | 0.6581          | 75.6026  |
| 0.2044        | 2.0   | 226  | 0.6616          | 87.1439  |
| 0.0757        | 3.0   | 339  | 0.6315          | 102.3375 |


### Framework versions

- PEFT 0.11.2.dev0
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1