metadata
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
base_model: openai/whisper-large-v3
model-index:
- name: whisper_finetune
results: []
whisper_finetune
This model is a fine-tuned version of openai/whisper-large-v3 on the aihub_100000 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0532
- Cer: 6.2644
- Wer: 23.9434
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-08
- train_batch_size: 16
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 1.5045 | 0.16 | 1000 | 1.4103 | 6.8826 | 26.6172 |
| 1.0745 | 0.32 | 2000 | 1.0532 | 6.2644 | 23.9434 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.17.0
- Tokenizers 0.15.2