42
This model is a fine-tuned version of microsoft/resnet-50 on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6777
- Accuracy: 0.8325
- Dt Accuracy: 0.8325
- Df Accuracy: 0.7692
- Unlearn Overall Accuracy: 0.3881
- Unlearn Time: None
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: 0.0002
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 391 | 0.6813 | 0.8662 | 0.2508 | 0.2508 | None |
| 1.6242 | 2.0 | 782 | 0.6915 | 0.8668 | 0.2499 | 0.2499 | None |
| 1.3877 | 3.0 | 1173 | 0.6780 | 0.876 | 0.2360 | 0.2360 | None |
| 1.2989 | 4.0 | 1564 | 0.6818 | 0.873 | 0.2407 | 0.2407 | None |
| 1.2989 | 5.0 | 1955 | 0.6872 | 0.8684 | 0.2477 | 0.2477 | None |
| 1.2337 | 6.0 | 2346 | 0.6632 | 0.8754 | 0.2372 | 0.2372 | None |
| 1.1757 | 7.0 | 2737 | 0.6685 | 0.8668 | 0.2504 | 0.2504 | None |
| 1.1367 | 8.0 | 3128 | 0.6793 | 0.8494 | 0.2767 | 0.2767 | None |
| 1.0964 | 9.0 | 3519 | 0.6773 | 0.8452 | 0.2828 | 0.2828 | None |
| 1.0964 | 10.0 | 3910 | 0.6683 | 0.8362 | 0.2960 | 0.2960 | None |
| 1.0586 | 11.0 | 4301 | 0.6754 | 0.8298 | 0.3053 | 0.3053 | None |
| 1.0437 | 12.0 | 4692 | 0.6678 | 0.8328 | 0.3010 | 0.3010 | None |
| 1.0108 | 13.0 | 5083 | 0.6734 | 0.8178 | 0.3223 | 0.3223 | None |
| 1.0108 | 14.0 | 5474 | 0.6724 | 0.799 | 0.3484 | 0.3484 | None |
| 0.9883 | 15.0 | 5865 | 0.6750 | 0.7944 | 0.3547 | 0.3547 | None |
| 0.9687 | 16.0 | 6256 | 0.6736 | 0.7898 | 0.3609 | 0.3609 | None |
| 0.9462 | 17.0 | 6647 | 0.6812 | 0.7748 | 0.3807 | 0.3807 | None |
| 0.94 | 18.0 | 7038 | 0.6761 | 0.78 | 0.3739 | 0.3739 | None |
| 0.94 | 19.0 | 7429 | 0.6754 | 0.772 | 0.3844 | 0.3844 | None |
| 0.925 | 20.0 | 7820 | 0.6777 | 0.7692 | 0.3881 | 0.3881 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2