metadata
library_name: transformers
language:
- ko
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- local
model-index:
- name: Whisper Turbo Ko v0.0.1
results: []
Whisper Turbo Ko v0.0.1
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the 상담 음성 데이터셋 0.0.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1478
- Cer: 3.3711
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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.1318 | 1.9417 | 1000 | 0.1500 | 4.1320 |
| 0.0513 | 3.8835 | 2000 | 0.1380 | 4.3269 |
| 0.0215 | 5.8252 | 3000 | 0.1387 | 3.6299 |
| 0.0042 | 7.7670 | 4000 | 0.1478 | 3.3711 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1