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: 0.1627
- Accuracy: 0.9574
- Dt Accuracy: 0.9574
- Df Accuracy: 0.9575
- Unlearn Overall Accuracy: 0.2491
- 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: 42
- 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 | 0.4694 | 0.8635 | 0.3730 | 0.3730 | None |
| 0.8835 | 2.0 | 782 | 0.3080 | 0.9045 | 0.3238 | 0.3238 | None |
| 0.7214 | 3.0 | 1173 | 0.2497 | 0.9365 | 0.2794 | 0.2794 | None |
| 0.6397 | 4.0 | 1564 | 0.2861 | 0.913 | 0.3125 | 0.3125 | None |
| 0.6397 | 5.0 | 1955 | 0.2243 | 0.944 | 0.2687 | 0.2687 | None |
| 0.5786 | 6.0 | 2346 | 0.2152 | 0.9365 | 0.2800 | 0.2800 | None |
| 0.5214 | 7.0 | 2737 | 0.1896 | 0.9525 | 0.2564 | 0.2564 | None |
| 0.4786 | 8.0 | 3128 | 0.1801 | 0.957 | 0.2497 | 0.2497 | None |
| 0.4333 | 9.0 | 3519 | 0.1667 | 0.952 | 0.2574 | 0.2574 | None |
| 0.4333 | 10.0 | 3910 | 0.1627 | 0.9575 | 0.2491 | 0.2491 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2