---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_finetune
  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_finetune

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3587
- Cer: 11.8692
- Wer: 34.6801

## 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: 32
- eval_batch_size: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer     | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:|
| 0.267         | 0.4   | 500  | 11.9783 | 0.3521          | 35.1998 |
| 0.2392        | 0.8   | 1000 | 12.1614 | 0.3495          | 34.9449 |
| 0.171         | 1.2   | 1500 | 12.0633 | 0.3516          | 35.2048 |
| 0.1744        | 1.6   | 2000 | 0.3553  | 12.2091         | 35.0598 |
| 0.1722        | 2.0   | 2500 | 0.3515  | 12.0222         | 34.5426 |
| 0.1192        | 2.4   | 3000 | 0.3594  | 12.2281         | 35.4796 |
| 0.1249        | 2.8   | 3500 | 0.3609  | 12.0137         | 34.8949 |
| 0.0858        | 3.2   | 4000 | 0.3587  | 11.8692         | 34.6801 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0