metadata
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: openai/whisper-base-Ko
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: kresnik/zeroth_korean
type: kresnik/zeroth_korean
config: clean
split: test
args: 'config: ko, split: test'
metrics:
- name: Wer
type: wer
value: 6.550218340611353
openai/whisper-base-Ko
This model is a fine-tuned version of openai/whisper-base on the kresnik/zeroth_korean dataset. It achieves the following results on the evaluation set:
- Loss: 0.0970
- Wer: 6.5502
- Cer: 2.9012
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: 5e-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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.3775 | 0.72 | 500 | 0.2690 | 22.8580 | 8.2443 |
| 0.1316 | 1.44 | 1000 | 0.1760 | 15.9012 | 6.8624 |
| 0.0658 | 2.16 | 1500 | 0.1285 | 10.6761 | 4.2753 |
| 0.0273 | 2.87 | 2000 | 0.1133 | 10.6309 | 5.0251 |
| 0.0112 | 3.59 | 2500 | 0.1040 | 8.0560 | 3.3448 |
| 0.0055 | 4.31 | 3000 | 0.1010 | 7.3633 | 3.2389 |
| 0.0024 | 5.03 | 3500 | 0.0979 | 6.6105 | 2.9837 |
| 0.0013 | 5.75 | 4000 | 0.0967 | 6.7309 | 2.9680 |
| 0.0009 | 6.47 | 4500 | 0.0967 | 6.6707 | 2.9405 |
| 0.0008 | 7.18 | 5000 | 0.0970 | 6.5502 | 2.9012 |
Framework versions
- Transformers 4.33.2
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.13.3