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SungBeom-whisper-small-ko-multiple-bg-v1
This model is a fine-tuned version of SungBeom/whisper-small-ko on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7993
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.4591 | 17.2414 | 500 | 0.8053 |
| 6.0259 | 34.4828 | 1000 | 0.8035 |
| 5.7577 | 51.7241 | 1500 | 0.8015 |
| 5.5694 | 68.9655 | 2000 | 0.7999 |
| 5.4494 | 86.2069 | 2500 | 0.7987 |
| 5.3702 | 103.4483 | 3000 | 0.7979 |
| 5.3229 | 120.6897 | 3500 | 0.7980 |
| 5.2742 | 137.9310 | 4000 | 0.7983 |
| 5.249 | 155.1724 | 4500 | 0.7990 |
| 5.2499 | 172.4138 | 5000 | 0.7993 |
Framework versions
- PEFT 0.10.0
- Transformers 4.41.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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