42
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: 0.2295
- Accuracy: 0.932
- Dt Accuracy: 0.932
- Df Accuracy: 0.857
- Unlearn Overall Accuracy: 0.3882
- 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: 0.001
- train_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|
| 1.3071 | 1.0 | 1563 | 0.9021 | 0.664 | 0 | 0 | None |
| 1.0605 | 2.0 | 3126 | 0.6188 | 0.759 | 0.4820 | 0.4820 | None |
| 0.9232 | 3.0 | 4689 | 0.5637 | 0.78 | 0.4638 | 0.4638 | None |
| 0.8288 | 4.0 | 6252 | 0.4544 | 0.836 | 0.4062 | 0.4062 | None |
| 0.7657 | 5.0 | 7815 | 0.4087 | 0.846 | 0.3957 | 0.3957 | None |
| 0.7128 | 6.0 | 9378 | 0.3632 | 0.861 | 0.3791 | 0.3791 | None |
| 0.6764 | 7.0 | 10941 | 0.3521 | 0.872 | 0.3653 | 0.3653 | None |
| 0.6419 | 8.0 | 12504 | 0.3354 | 0.884 | 0.3502 | 0.3502 | None |
| 0.6108 | 9.0 | 14067 | 0.2890 | 0.895 | 0.3364 | 0.3364 | None |
| 0.5749 | 10.0 | 15630 | 0.2841 | 0.892 | 0.3407 | 0.3407 | None |
| 0.554 | 11.0 | 17193 | 0.2794 | 0.893 | 0.3396 | 0.3396 | None |
| 0.5309 | 12.0 | 18756 | 0.2615 | 0.901 | 0.3290 | 0.3290 | None |
| 0.5065 | 13.0 | 20319 | 0.2496 | 0.906 | 0.3224 | 0.3224 | None |
| 0.4798 | 14.0 | 21882 | 0.2532 | 0.893 | 0.3403 | 0.3403 | None |
| 0.469 | 15.0 | 23445 | 0.2496 | 0.894 | 0.3391 | 0.3391 | None |
| 0.4373 | 16.0 | 25008 | 0.2338 | 0.904 | 0.3256 | 0.3256 | None |
| 0.4242 | 17.0 | 26571 | 0.2514 | 0.854 | 0.3914 | 0.3914 | None |
| 0.4149 | 18.0 | 28134 | 0.2415 | 0.856 | 0.3891 | 0.3891 | None |
| 0.3832 | 19.0 | 29697 | 0.2304 | 0.867 | 0.3752 | 0.3752 | None |
| 0.3754 | 20.0 | 31260 | 0.2295 | 0.857 | 0.3882 | 0.3882 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2