---
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- GGarri/customdataset
metrics:
- wer
model-index:
- name: Whisper Small ko
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: customdata
      type: GGarri/customdataset
    metrics:
    - name: Wer
      type: wer
      value: 2.590564448188711
---

<!-- 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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the customdata dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0041
- Cer: 2.4925
- Wer: 2.5906

## 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: 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 3.4996        | 0.89  | 25   | 3.1447          | 75.5887 | 19.7136 |
| 2.655         | 1.79  | 50   | 2.1647          | 74.1483 | 18.1761 |
| 1.7168        | 2.68  | 75   | 1.2822          | 71.8061 | 17.2283 |
| 0.9261        | 3.57  | 100  | 0.6754          | 63.5396 | 51.5586 |
| 0.4707        | 4.46  | 125  | 0.3511          | 40.5686 | 37.3842 |
| 0.2485        | 5.36  | 150  | 0.2027          | 27.9309 | 25.6950 |
| 0.1463        | 6.25  | 175  | 0.1315          | 24.7119 | 23.9890 |
| 0.1022        | 7.14  | 200  | 0.0881          | 21.1924 | 19.9242 |
| 0.0642        | 8.04  | 225  | 0.0501          | 18.7625 | 17.6917 |
| 0.0249        | 8.93  | 250  | 0.0144          | 27.2044 | 26.3479 |
| 0.0056        | 9.82  | 275  | 0.0082          | 12.4749 | 11.9208 |
| 0.0036        | 10.71 | 300  | 0.0067          | 8.5922  | 8.7616  |
| 0.0037        | 11.61 | 325  | 0.0119          | 6.4003  | 6.1500  |
| 0.0021        | 12.5  | 350  | 0.0054          | 3.7450  | 3.6015  |
| 0.0013        | 13.39 | 375  | 0.0052          | 2.8557  | 3.0329  |
| 0.0017        | 14.29 | 400  | 0.0062          | 9.0681  | 8.3825  |
| 0.0016        | 15.18 | 425  | 0.0081          | 4.9098  | 5.3917  |
| 0.0012        | 16.07 | 450  | 0.0108          | 14.5541 | 13.3530 |
| 0.0014        | 16.96 | 475  | 0.0033          | 3.4068  | 3.4120  |
| 0.0005        | 17.86 | 500  | 0.0041          | 2.4925  | 2.5906  |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2