87
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: 10.2401
- Accuracy: 0.0496
- Dt Accuracy: 0.0496
- Df Accuracy: 0.0482
- 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: 87
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | 79 | 1.0297 | 0.799 | 0.3419 | 0.3419 | None |
| 0.0 | 2.0 | 158 | 2.0581 | 0.5964 | 0 | 0 | None |
| 0.0 | 3.0 | 237 | 3.6253 | 0.3978 | 0 | 0 | None |
| 0.0 | 4.0 | 316 | 5.4675 | 0.2462 | 0 | 0 | None |
| 0.0 | 5.0 | 395 | 6.6299 | 0.1686 | 0 | 0 | None |
| 0.0 | 6.0 | 474 | 7.5614 | 0.1164 | 0 | 0 | None |
| 0.0 | 7.0 | 553 | 8.7485 | 0.076 | 0 | 0 | None |
| 0.0 | 8.0 | 632 | 8.3419 | 0.057 | 0 | 0 | None |
| 0.0 | 9.0 | 711 | 9.3853 | 0.0498 | 0 | 0 | None |
| 0.0 | 10.0 | 790 | 10.2401 | 0.0482 | 0 | 0 | None |
Framework versions
- Transformers 4.48.0
- Pytorch 2.2.2+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0