---
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: 0.4807
- Cer: 14.7381
- Wer: 40.8215

## 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 | Validation Loss | Cer     | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.2038        | 0.4   | 500  | 0.4405          | 13.6475 | 39.1975 |
| 0.1892        | 0.8   | 1000 | 0.4491          | 14.5230 | 40.5892 |
| 0.1218        | 1.2   | 1500 | 0.4710          | 14.4216 | 40.2519 |
| 0.1227        | 1.6   | 2000 | 0.4879          | 14.3981 | 40.1969 |
| 0.1311        | 2.0   | 2500 | 0.4638          | 14.6655 | 40.9614 |
| 0.0945        | 2.4   | 3000 | 0.4783          | 14.6635 | 40.9190 |
| 0.0874        | 2.8   | 3500 | 0.4743          | 14.3360 | 40.4492 |
| 0.0759        | 3.2   | 4000 | 0.4807          | 14.7381 | 40.8215 |


### Framework versions

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