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: -61.2603
- Accuracy: 0.0145
- Dt Accuracy: 0.0145
- Df Accuracy: 0.0132
- Unlearn Overall Accuracy: 0
- 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: 5e-05
- 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 | 40 | -0.6705 | 0.8614 | 0.2576 | 0.2576 | None |
| No log | 2.0 | 80 | -1.1856 | 0.7334 | 0.4182 | 0.4182 | None |
| No log | 3.0 | 120 | -3.0241 | 0.4682 | 0 | 0 | None |
| No log | 4.0 | 160 | -6.8932 | 0.2358 | 0 | 0 | None |
| No log | 5.0 | 200 | -11.5720 | 0.1004 | 0 | 0 | None |
| No log | 6.0 | 240 | -16.6897 | 0.0524 | 0 | 0 | None |
| No log | 7.0 | 280 | -21.7166 | 0.035 | 0 | 0 | None |
| No log | 8.0 | 320 | -26.8608 | 0.0274 | 0 | 0 | None |
| No log | 9.0 | 360 | -31.0666 | 0.0212 | 0 | 0 | None |
| No log | 10.0 | 400 | -38.7816 | 0.0186 | 0 | 0 | None |
| No log | 11.0 | 440 | -41.5065 | 0.017 | 0 | 0 | None |
| No log | 12.0 | 480 | -45.3635 | 0.017 | 0 | 0 | None |
| -18.2648 | 13.0 | 520 | -49.5281 | 0.016 | 0 | 0 | None |
| -18.2648 | 14.0 | 560 | -53.6067 | 0.0154 | 0 | 0 | None |
| -18.2648 | 15.0 | 600 | -50.5046 | 0.0158 | 0 | 0 | None |
| -18.2648 | 16.0 | 640 | -55.5001 | 0.0148 | 0 | 0 | None |
| -18.2648 | 17.0 | 680 | -55.9571 | 0.0148 | 0 | 0 | None |
| -18.2648 | 18.0 | 720 | -53.0937 | 0.015 | 0 | 0 | None |
| -18.2648 | 19.0 | 760 | -54.5232 | 0.0144 | 0 | 0 | None |
| -18.2648 | 20.0 | 800 | -61.2603 | 0.0132 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2