87
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: 0.5404
- Accuracy: 0.8408
- Dt Accuracy: 0.8408
- Df Accuracy: 0.895
- Unlearn Overall Accuracy: 0.1699
- 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- seed: 87
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| 1.1594 | 1.0 | 391 | 0.5830 | 0.898 | 0.1679 | 0.1679 | None |
| 1.1158 | 2.0 | 782 | 0.5704 | 0.899 | 0.1673 | 0.1673 | None |
| 1.0827 | 3.0 | 1173 | 0.5639 | 0.899 | 0.1673 | 0.1673 | None |
| 1.05 | 4.0 | 1564 | 0.5543 | 0.888 | 0.1748 | 0.1748 | None |
| 1.0484 | 5.0 | 1955 | 0.5518 | 0.901 | 0.1658 | 0.1658 | None |
| 1.031 | 6.0 | 2346 | 0.5491 | 0.886 | 0.1761 | 0.1761 | None |
| 1.001 | 7.0 | 2737 | 0.5433 | 0.894 | 0.1706 | 0.1706 | None |
| 0.9714 | 8.0 | 3128 | 0.5412 | 0.893 | 0.1712 | 0.1712 | None |
| 0.9789 | 9.0 | 3519 | 0.5413 | 0.894 | 0.1705 | 0.1705 | None |
| 0.9602 | 10.0 | 3910 | 0.5404 | 0.895 | 0.1699 | 0.1699 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2