metadata
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
- whisper-event
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: Whisper Small Korean
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Zeroth Korean
type: kresnik/zeroth_korean
config: clean
split: test
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 6.761029965366662
Whisper Small Korean
This model is a fine-tuned version of openai/whisper-small on the Zeroth Korean dataset. It achieves the following results on the evaluation set:
- Loss: 0.0899
- Wer: 6.7610
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: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1277 | 0.72 | 1000 | 0.1489 | 12.2271 |
0.0379 | 1.44 | 2000 | 0.1053 | 6.7159 |
0.0138 | 2.16 | 3000 | 0.0918 | 6.0382 |
0.0141 | 2.87 | 4000 | 0.0899 | 6.7610 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0a0+d0d6b1f
- Datasets 2.7.1
- Tokenizers 0.13.2