---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
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_20000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4938
- Cer: 14.1359

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3736        | 0.8   | 500  | 0.4641          | 15.1146 |
| 0.2685        | 1.6   | 1000 | 0.4525          | 14.3150 |
| 0.1929        | 2.4   | 1500 | 0.4424          | 14.0470 |
| 0.1241        | 3.2   | 2000 | 0.4584          | 13.8724 |
| 0.1347        | 4.0   | 2500 | 0.4554          | 13.9110 |
| 0.0944        | 4.8   | 3000 | 0.4693          | 14.0391 |
| 0.0761        | 5.6   | 3500 | 0.4851          | 14.1281 |
| 0.0606        | 6.4   | 4000 | 0.4938          | 14.1359 |


### Framework versions

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