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: 0.6432
- Accuracy: 0.8376
- Dt Accuracy: 0.8376
- Df Accuracy: 0.7847
- Unlearn Overall Accuracy: 0.3674
- 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 | 0.6640 | 0.8718 | 0.2424 | 0.2424 | None |
| 1.5324 | 2.0 | 782 | 0.6619 | 0.869 | 0.2467 | 0.2467 | None |
| 1.338 | 3.0 | 1173 | 0.6555 | 0.874 | 0.2392 | 0.2392 | None |
| 1.2599 | 4.0 | 1564 | 0.6457 | 0.8778 | 0.2334 | 0.2334 | None |
| 1.2599 | 5.0 | 1955 | 0.6594 | 0.8705 | 0.2446 | 0.2446 | None |
| 1.1936 | 6.0 | 2346 | 0.6472 | 0.8675 | 0.2492 | 0.2492 | None |
| 1.1308 | 7.0 | 2737 | 0.6317 | 0.877 | 0.2347 | 0.2347 | None |
| 1.0909 | 8.0 | 3128 | 0.6528 | 0.866 | 0.2517 | 0.2517 | None |
| 1.0533 | 9.0 | 3519 | 0.6384 | 0.8622 | 0.2575 | 0.2575 | None |
| 1.0533 | 10.0 | 3910 | 0.6374 | 0.847 | 0.2802 | 0.2802 | None |
| 1.015 | 11.0 | 4301 | 0.6474 | 0.8407 | 0.2895 | 0.2895 | None |
| 0.9935 | 12.0 | 4692 | 0.6396 | 0.831 | 0.3035 | 0.3035 | None |
| 0.9688 | 13.0 | 5083 | 0.6372 | 0.8247 | 0.3123 | 0.3123 | None |
| 0.9688 | 14.0 | 5474 | 0.6448 | 0.8133 | 0.3288 | 0.3288 | None |
| 0.9343 | 15.0 | 5865 | 0.6395 | 0.8047 | 0.3404 | 0.3404 | None |
| 0.9257 | 16.0 | 6256 | 0.6405 | 0.8015 | 0.3448 | 0.3448 | None |
| 0.9084 | 17.0 | 6647 | 0.6492 | 0.789 | 0.3617 | 0.3617 | None |
| 0.885 | 18.0 | 7038 | 0.6422 | 0.7847 | 0.3675 | 0.3675 | None |
| 0.885 | 19.0 | 7429 | 0.6404 | 0.787 | 0.3643 | 0.3643 | None |
| 0.8848 | 20.0 | 7820 | 0.6432 | 0.7847 | 0.3674 | 0.3674 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2