42
This model is a fine-tuned version of microsoft/resnet-50 on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6295
- Accuracy: 0.8406
- Dt Accuracy: 0.8406
- Df Accuracy: 0.7405
- Unlearn Overall Accuracy: 0.4239
- 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: 0.0002
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 391 | 0.6519 | 0.7123 | 0.4575 | 0.4575 | None |
| 1.5454 | 2.0 | 782 | 0.6434 | 0.72 | 0.4484 | 0.4484 | None |
| 1.3647 | 3.0 | 1173 | 0.6586 | 0.7153 | 0.4543 | 0.4543 | None |
| 1.2856 | 4.0 | 1564 | 0.6335 | 0.724 | 0.4442 | 0.4442 | None |
| 1.2856 | 5.0 | 1955 | 0.6476 | 0.7285 | 0.4387 | 0.4387 | None |
| 1.2233 | 6.0 | 2346 | 0.6329 | 0.73 | 0.4374 | 0.4374 | None |
| 1.1651 | 7.0 | 2737 | 0.6232 | 0.737 | 0.4286 | 0.4286 | None |
| 1.1337 | 8.0 | 3128 | 0.6422 | 0.7425 | 0.4220 | 0.4220 | None |
| 1.1046 | 9.0 | 3519 | 0.6293 | 0.735 | 0.4311 | 0.4311 | None |
| 1.1046 | 10.0 | 3910 | 0.6310 | 0.7462 | 0.4174 | 0.4174 | None |
| 1.0724 | 11.0 | 4301 | 0.6338 | 0.747 | 0.4165 | 0.4165 | None |
| 1.0551 | 12.0 | 4692 | 0.6299 | 0.7498 | 0.4127 | 0.4127 | None |
| 1.0333 | 13.0 | 5083 | 0.6252 | 0.7522 | 0.4093 | 0.4093 | None |
| 1.0333 | 14.0 | 5474 | 0.6348 | 0.7365 | 0.4290 | 0.4290 | None |
| 1.0049 | 15.0 | 5865 | 0.6283 | 0.7418 | 0.4226 | 0.4226 | None |
| 1.0002 | 16.0 | 6256 | 0.6279 | 0.7445 | 0.4189 | 0.4189 | None |
| 0.986 | 17.0 | 6647 | 0.6359 | 0.7542 | 0.4069 | 0.4069 | None |
| 0.967 | 18.0 | 7038 | 0.6286 | 0.7492 | 0.4130 | 0.4130 | None |
| 0.967 | 19.0 | 7429 | 0.6261 | 0.7482 | 0.4140 | 0.4140 | None |
| 0.9686 | 20.0 | 7820 | 0.6295 | 0.7405 | 0.4239 | 0.4239 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2