---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- didiudom94/gentlemen
metrics:
- bleu
model-index:
- name: Whisper Small Ko to En
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Gentlemen
      type: didiudom94/gentlemen
      args: 'split: train'
    metrics:
    - name: Bleu
      type: bleu
      value: 0.1392438982977928
---

<!-- 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 Small Ko to En

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Gentlemen dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3270
- Bleu: 0.1392

## 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: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.8182        | 0.2253 | 1000 | 1.6561          | 0.1004 |
| 1.4212        | 0.4507 | 2000 | 1.4204          | 0.1195 |
| 1.3578        | 0.6760 | 3000 | 1.3638          | 0.1320 |
| 1.3446        | 0.9013 | 4000 | 1.3265          | 0.1356 |
| 0.9391        | 1.1266 | 5000 | 1.3270          | 0.1392 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3