face_poofing_detection
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6273
- Accuracy: 0.9871
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.3243 | 0.9846 | 48 | 5.6154 | 0.8919 |
| 4.4794 | 1.9897 | 97 | 4.3516 | 0.9202 |
| 3.8293 | 2.9949 | 146 | 3.6687 | 0.9730 |
| 3.2121 | 4.0 | 195 | 3.1092 | 0.9820 |
| 2.733 | 4.9846 | 243 | 2.6919 | 0.9743 |
| 2.3114 | 5.9897 | 292 | 2.2633 | 0.9923 |
| 1.9962 | 6.9949 | 341 | 1.9594 | 0.9923 |
| 1.7789 | 8.0 | 390 | 1.7641 | 0.9897 |
| 1.6642 | 8.9846 | 438 | 1.6506 | 0.9910 |
| 1.6005 | 9.8462 | 480 | 1.6273 | 0.9871 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21k