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: 0.5745
- Accuracy: 0.8439
- Dt Accuracy: 0.8439
- Df Accuracy: 0.732
- Unlearn Overall Accuracy: 0.4340
- 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 | 0.6046 | 0.718 | 0.4511 | 0.4511 | None |
| 1.3328 | 2.0 | 782 | 0.5995 | 0.717 | 0.4526 | 0.4526 | None |
| 1.2184 | 3.0 | 1173 | 0.6007 | 0.7195 | 0.4495 | 0.4495 | None |
| 1.1638 | 4.0 | 1564 | 0.5948 | 0.7205 | 0.4486 | 0.4486 | None |
| 1.1638 | 5.0 | 1955 | 0.5900 | 0.71 | 0.4614 | 0.4614 | None |
| 1.1147 | 6.0 | 2346 | 0.5947 | 0.72 | 0.4495 | 0.4495 | None |
| 1.0636 | 7.0 | 2737 | 0.5808 | 0.737 | 0.4284 | 0.4284 | None |
| 1.0156 | 8.0 | 3128 | 0.5920 | 0.7295 | 0.4377 | 0.4377 | None |
| 0.9939 | 9.0 | 3519 | 0.5792 | 0.7305 | 0.4363 | 0.4363 | None |
| 0.9939 | 10.0 | 3910 | 0.5799 | 0.7255 | 0.4421 | 0.4421 | None |
| 0.9656 | 11.0 | 4301 | 0.5821 | 0.733 | 0.4333 | 0.4333 | None |
| 0.954 | 12.0 | 4692 | 0.5798 | 0.7385 | 0.4261 | 0.4261 | None |
| 0.9323 | 13.0 | 5083 | 0.5745 | 0.7465 | 0.4163 | 0.4163 | None |
| 0.9323 | 14.0 | 5474 | 0.5799 | 0.748 | 0.4146 | 0.4146 | None |
| 0.9093 | 15.0 | 5865 | 0.5742 | 0.7385 | 0.4262 | 0.4262 | None |
| 0.8997 | 16.0 | 6256 | 0.5721 | 0.741 | 0.4228 | 0.4228 | None |
| 0.8874 | 17.0 | 6647 | 0.5768 | 0.735 | 0.4304 | 0.4304 | None |
| 0.8669 | 18.0 | 7038 | 0.5755 | 0.7525 | 0.4087 | 0.4087 | None |
| 0.8669 | 19.0 | 7429 | 0.5711 | 0.7285 | 0.4382 | 0.4382 | None |
| 0.8662 | 20.0 | 7820 | 0.5745 | 0.732 | 0.4340 | 0.4340 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2