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---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- GGarri/241109_newdata
metrics:
- wer
model-index:
- name: Whisper Small ko
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: customdata
type: GGarri/241109_newdata
metrics:
- name: Wer
type: wer
value: 1.3576367064739157
---
<!-- 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: 0.0892
- Cer: 1.7222
- Wer: 1.3576
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 1.0297 | 1.9231 | 100 | 0.8542 | 5.7071 | 5.2420 |
| 0.2945 | 3.8462 | 200 | 0.2539 | 3.1678 | 2.6524 |
| 0.022 | 5.7692 | 300 | 0.0721 | 2.3633 | 1.8982 |
| 0.0066 | 7.6923 | 400 | 0.0744 | 2.1999 | 1.7348 |
| 0.0055 | 9.6154 | 500 | 0.0681 | 1.9485 | 1.5462 |
| 0.0021 | 11.5385 | 600 | 0.0743 | 2.1622 | 1.7096 |
| 0.0019 | 13.4615 | 700 | 0.0723 | 2.1747 | 1.7096 |
| 0.0005 | 15.3846 | 800 | 0.0733 | 1.8856 | 1.4833 |
| 0.0001 | 17.3077 | 900 | 0.0738 | 1.9233 | 1.4582 |
| 0.0001 | 19.2308 | 1000 | 0.0748 | 1.9233 | 1.4582 |
| 0.0001 | 21.1538 | 1100 | 0.0759 | 1.8353 | 1.4708 |
| 0.0001 | 23.0769 | 1200 | 0.0765 | 1.8102 | 1.4456 |
| 0.0001 | 25.0 | 1300 | 0.0770 | 1.7976 | 1.4331 |
| 0.0001 | 26.9231 | 1400 | 0.0773 | 1.7976 | 1.4331 |
| 0.0001 | 28.8462 | 1500 | 0.0776 | 1.7976 | 1.4331 |
| 0.0001 | 30.7692 | 1600 | 0.0780 | 1.7976 | 1.4331 |
| 0.0001 | 32.6923 | 1700 | 0.0782 | 1.7976 | 1.4331 |
| 0.0001 | 34.6154 | 1800 | 0.0786 | 1.7850 | 1.4205 |
| 0.0001 | 36.5385 | 1900 | 0.0790 | 1.7850 | 1.4205 |
| 0.0001 | 38.4615 | 2000 | 0.0794 | 1.7599 | 1.3953 |
| 0.0001 | 40.3846 | 2100 | 0.0804 | 1.7599 | 1.3953 |
| 0.0001 | 42.3077 | 2200 | 0.0811 | 1.7599 | 1.3953 |
| 0.0 | 44.2308 | 2300 | 0.0816 | 1.7599 | 1.3953 |
| 0.0 | 46.1538 | 2400 | 0.0821 | 1.7473 | 1.3828 |
| 0.0 | 48.0769 | 2500 | 0.0825 | 1.7473 | 1.3828 |
| 0.0 | 50.0 | 2600 | 0.0829 | 1.7473 | 1.3828 |
| 0.0 | 51.9231 | 2700 | 0.0832 | 1.7473 | 1.3828 |
| 0.0 | 53.8462 | 2800 | 0.0836 | 1.7473 | 1.3828 |
| 0.0 | 55.7692 | 2900 | 0.0840 | 1.7473 | 1.3828 |
| 0.0 | 57.6923 | 3000 | 0.0843 | 1.7473 | 1.3828 |
| 0.0 | 59.6154 | 3100 | 0.0846 | 1.7473 | 1.3828 |
| 0.0 | 61.5385 | 3200 | 0.0849 | 1.7473 | 1.3828 |
| 0.0 | 63.4615 | 3300 | 0.0853 | 1.7473 | 1.3828 |
| 0.0 | 65.3846 | 3400 | 0.0855 | 1.7348 | 1.3702 |
| 0.0 | 67.3077 | 3500 | 0.0858 | 1.7348 | 1.3702 |
| 0.0 | 69.2308 | 3600 | 0.0860 | 1.7348 | 1.3702 |
| 0.0 | 71.1538 | 3700 | 0.0863 | 1.7348 | 1.3702 |
| 0.0 | 73.0769 | 3800 | 0.0866 | 1.7348 | 1.3702 |
| 0.0 | 75.0 | 3900 | 0.0868 | 1.7348 | 1.3702 |
| 0.0 | 76.9231 | 4000 | 0.0870 | 1.7348 | 1.3702 |
| 0.0 | 78.8462 | 4100 | 0.0877 | 1.7473 | 1.3828 |
| 0.0 | 80.7692 | 4200 | 0.0881 | 1.7222 | 1.3576 |
| 0.0 | 82.6923 | 4300 | 0.0884 | 1.7222 | 1.3576 |
| 0.0 | 84.6154 | 4400 | 0.0886 | 1.7222 | 1.3576 |
| 0.0 | 86.5385 | 4500 | 0.0888 | 1.7222 | 1.3576 |
| 0.0 | 88.4615 | 4600 | 0.0889 | 1.7222 | 1.3576 |
| 0.0 | 90.3846 | 4700 | 0.0890 | 1.7222 | 1.3576 |
| 0.0 | 92.3077 | 4800 | 0.0891 | 1.7222 | 1.3576 |
| 0.0 | 94.2308 | 4900 | 0.0891 | 1.7222 | 1.3576 |
| 0.0 | 96.1538 | 5000 | 0.0892 | 1.7222 | 1.3576 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.4.0
- Datasets 2.18.0
- Tokenizers 0.20.3
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