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---
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: 6.9309637730690365
---
<!-- 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: 0.0268
- Cer: 6.5045
- Wer: 6.9310
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 3.6391 | 0.54 | 25 | 3.3230 | 83.6552 | 35.4340 |
| 2.7648 | 1.09 | 50 | 2.3011 | 81.2725 | 31.6473 |
| 1.8272 | 1.63 | 75 | 1.4490 | 85.9460 | 43.8688 |
| 1.0827 | 2.17 | 100 | 0.8137 | 72.8033 | 59.1524 |
| 0.6201 | 2.72 | 125 | 0.4756 | 50.5476 | 49.9522 |
| 0.3539 | 3.26 | 150 | 0.3005 | 31.1094 | 31.5926 |
| 0.2358 | 3.8 | 175 | 0.1969 | 29.5962 | 31.3192 |
| 0.1501 | 4.35 | 200 | 0.1352 | 21.1688 | 21.7772 |
| 0.0967 | 4.89 | 225 | 0.0846 | 18.6941 | 19.0431 |
| 0.0471 | 5.43 | 250 | 0.0350 | 18.3931 | 18.9200 |
| 0.0162 | 5.98 | 275 | 0.0335 | 18.9616 | 19.5215 |
| 0.0121 | 6.52 | 300 | 0.0324 | 14.1293 | 15.5707 |
| 0.011 | 7.07 | 325 | 0.0261 | 12.9755 | 14.3267 |
| 0.0078 | 7.61 | 350 | 0.0223 | 9.3220 | 10.5400 |
| 0.0075 | 8.15 | 375 | 0.0217 | 5.8106 | 6.5482 |
| 0.0052 | 8.7 | 400 | 0.0208 | 7.9926 | 8.6945 |
| 0.0048 | 9.24 | 425 | 0.0213 | 5.3424 | 5.7280 |
| 0.0053 | 9.78 | 450 | 0.0212 | 7.5328 | 7.9973 |
| 0.004 | 10.33 | 475 | 0.0213 | 5.7186 | 5.9740 |
| 0.0054 | 10.87 | 500 | 0.0268 | 6.5045 | 6.9310 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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