metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MobileNetV2-KD-VGGFace
results: []
license: mit
MobileNetV2-KD-VGGFace
This model is trained via KD from ViT on first 50k samples of VGGFace dataset. It achieves the following results on the evaluation set:
- Loss: 0.4919
- Accuracy: 0.7836
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-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7506 | 1.0 | 1667 | 2.2449 | 0.0726 |
| 2.105 | 2.0 | 3334 | 1.6904 | 0.2493 |
| 1.6544 | 3.0 | 5001 | 1.3206 | 0.4043 |
| 1.3357 | 4.0 | 6668 | 1.0675 | 0.5078 |
| 1.1104 | 5.0 | 8335 | 0.9302 | 0.5582 |
| 0.9287 | 6.0 | 10002 | 0.8738 | 0.5972 |
| 0.7899 | 7.0 | 11669 | 0.7972 | 0.6388 |
| 0.6738 | 8.0 | 13336 | 0.7074 | 0.6822 |
| 0.5803 | 9.0 | 15003 | 0.6630 | 0.7009 |
| 0.5038 | 10.0 | 16670 | 0.5855 | 0.735 |
| 0.4366 | 11.0 | 18337 | 0.5761 | 0.7415 |
| 0.3762 | 12.0 | 20004 | 0.5642 | 0.7496 |
| 0.3321 | 13.0 | 21671 | 0.5373 | 0.7652 |
| 0.2916 | 14.0 | 23338 | 0.5314 | 0.7625 |
| 0.2615 | 15.0 | 25005 | 0.6206 | 0.7281 |
| 0.2357 | 16.0 | 26672 | 0.5437 | 0.763 |
| 0.2153 | 17.0 | 28339 | 0.5335 | 0.763 |
| 0.1986 | 18.0 | 30006 | 0.4892 | 0.7869 |
| 0.1866 | 19.0 | 31673 | 0.5368 | 0.7645 |
| 0.1765 | 20.0 | 33340 | 0.4919 | 0.7836 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+rocm6.0
- Datasets 2.20.0
- Tokenizers 0.19.1