metadata
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- whisper-event
- generated_from_trainer
datasets:
- kresnik/zeroth_korean
metrics:
- wer
model-index:
- name: Whisper Medium Korean
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Zeroth Korean
type: kresnik/zeroth_korean
config: clean
split: test
args: 'split: test'
metrics:
- type: wer
value: 3.6440295136274656
name: Test Wer
Whisper Medium Korean
This model is a fine-tuned version of openai/whisper-medium on the Zeroth Korean dataset. It achieves the following results on the evaluation set:
- Loss: 0.0727
- Wer: 3.6440
- Cer: 1.4840
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Wer | Cer |
|---|---|---|---|---|---|
| 0.0873 | 0.72 | 1000 | 0.1086 | 7.7549 | 2.5597 |
| 0.0258 | 1.44 | 2000 | 0.0805 | 4.5475 | 1.7588 |
| 0.0091 | 2.16 | 3000 | 0.0719 | 3.7946 | 1.5664 |
| 0.0086 | 2.88 | 4000 | 0.0704 | 3.5537 | 1.5232 |
| 0.0019 | 3.59 | 5000 | 0.0727 | 3.6440 | 1.4840 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0a0+d0d6b1f
- Datasets 2.7.1
- Tokenizers 0.13.2