87
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: 0.1189
- Accuracy: 0.9665
- Dt Accuracy: 0.9665
- Df Accuracy: 0.9
- Unlearn Overall Accuracy: 0.3333
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 391 | 0.1225 | 0.882 | 0.3576 | 0.3576 | None |
| 0.4549 | 2.0 | 782 | 0.1193 | 0.879 | 0.3619 | 0.3619 | None |
| 0.4272 | 3.0 | 1173 | 0.1162 | 0.89 | 0.3471 | 0.3471 | None |
| 0.412 | 4.0 | 1564 | 0.1196 | 0.894 | 0.3415 | 0.3415 | None |
| 0.412 | 5.0 | 1955 | 0.1197 | 0.884 | 0.3552 | 0.3552 | None |
| 0.4062 | 6.0 | 2346 | 0.1211 | 0.878 | 0.3632 | 0.3632 | None |
| 0.3939 | 7.0 | 2737 | 0.1191 | 0.874 | 0.3686 | 0.3686 | None |
| 0.3874 | 8.0 | 3128 | 0.1192 | 0.889 | 0.3485 | 0.3485 | None |
| 0.3871 | 9.0 | 3519 | 0.1179 | 0.878 | 0.3633 | 0.3633 | None |
| 0.3871 | 10.0 | 3910 | 0.1189 | 0.9 | 0.3333 | 0.3333 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2