87
This model is a fine-tuned version of microsoft/resnet-34 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1611
- Accuracy: 0.958
- Dt Accuracy: 0.958
- Df Accuracy: 0.9455
- Unlearn Overall Accuracy: 0.2673
- 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: 0.0005
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 391 | 0.4014 | 0.881 | 0.3530 | 0.3530 | None |
| 0.8855 | 2.0 | 782 | 0.3984 | 0.8775 | 0.3575 | 0.3575 | None |
| 0.7295 | 3.0 | 1173 | 0.2906 | 0.9215 | 0.3006 | 0.3006 | None |
| 0.6386 | 4.0 | 1564 | 0.2438 | 0.928 | 0.2918 | 0.2918 | None |
| 0.6386 | 5.0 | 1955 | 0.2251 | 0.943 | 0.2701 | 0.2701 | None |
| 0.5855 | 6.0 | 2346 | 0.2036 | 0.946 | 0.2660 | 0.2660 | None |
| 0.5229 | 7.0 | 2737 | 0.1949 | 0.943 | 0.2706 | 0.2706 | None |
| 0.4837 | 8.0 | 3128 | 0.1817 | 0.944 | 0.2694 | 0.2694 | None |
| 0.4406 | 9.0 | 3519 | 0.1658 | 0.9485 | 0.2627 | 0.2627 | None |
| 0.4406 | 10.0 | 3910 | 0.1611 | 0.9455 | 0.2673 | 0.2673 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2