metadata
base_model: openai/whisper-tiny
datasets:
- mozilla-foundation/common_voice_17_0
language:
- ko
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Tiny Ko - Roooy
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ko
split: None
args: 'config: ko, split: train+valid & test'
metrics:
- type: wer
value: 61.8411000763942
name: Wer
Whisper Tiny Ko - Roooy
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3774
- Cer: 30.0833
- Wer: 61.8411
- Cer Wer Avg: 45.9622
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: 16
- 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: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Cer Wer Avg |
---|---|---|---|---|---|---|
0.0005 | 22.2222 | 1000 | 1.0691 | 27.3648 | 58.8235 | 43.0942 |
0.0002 | 44.4444 | 2000 | 1.1396 | 30.6350 | 62.9488 | 46.7919 |
0.0001 | 66.6667 | 3000 | 1.1884 | 31.1967 | 63.5982 | 47.3974 |
0.0001 | 88.8889 | 4000 | 1.2300 | 31.4776 | 64.2093 | 47.8435 |
0.0 | 111.1111 | 5000 | 1.2656 | 31.7284 | 64.7441 | 48.2362 |
0.0 | 133.3333 | 6000 | 1.2993 | 32.1396 | 65.0497 | 48.5946 |
0.0 | 155.5556 | 7000 | 1.3272 | 32.3804 | 64.9351 | 48.6577 |
0.0 | 177.7778 | 8000 | 1.3518 | 29.9829 | 61.8029 | 45.8929 |
0.0 | 200.0 | 9000 | 1.3693 | 30.1836 | 61.8793 | 46.0314 |
0.0 | 222.2222 | 10000 | 1.3774 | 30.0833 | 61.8411 | 45.9622 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1