100
This model is a fine-tuned version of microsoft/resnet-50 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2012
- Accuracy: 0.9667
- Dt Accuracy: 0.9667
- Df Accuracy: 0.8922
- Unlearn Overall Accuracy: 0.3441
- 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: 100
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | 0.2108 | 0.8748 | 0.3672 | 0.3672 | None |
| 0.7212 | 2.0 | 782 | 0.2146 | 0.8834 | 0.3558 | 0.3558 | None |
| 0.6496 | 3.0 | 1173 | 0.2017 | 0.8816 | 0.3584 | 0.3584 | None |
| 0.627 | 4.0 | 1564 | 0.2085 | 0.8888 | 0.3485 | 0.3485 | None |
| 0.627 | 5.0 | 1955 | 0.2006 | 0.8838 | 0.3554 | 0.3554 | None |
| 0.6109 | 6.0 | 2346 | 0.1961 | 0.8864 | 0.3520 | 0.3520 | None |
| 0.5955 | 7.0 | 2737 | 0.2089 | 0.8902 | 0.3466 | 0.3466 | None |
| 0.5843 | 8.0 | 3128 | 0.2035 | 0.896 | 0.3387 | 0.3387 | None |
| 0.5788 | 9.0 | 3519 | 0.2028 | 0.9034 | 0.3285 | 0.3285 | None |
| 0.5788 | 10.0 | 3910 | 0.2012 | 0.8922 | 0.3441 | 0.3441 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.21.0