13
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: 12.1434
- Accuracy: 0.0118
- Dt Accuracy: 0.0118
- Df Accuracy: 0.0125
- 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- seed: 13
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | 63 | 1.6647 | 0.6685 | 0 | 0 | None |
| 0.0 | 2.0 | 126 | 4.6809 | 0.3147 | 0 | 0 | None |
| 0.0 | 3.0 | 189 | 7.6076 | 0.1245 | 0 | 0 | None |
| 0.0 | 4.0 | 252 | 8.5717 | 0.0425 | 0 | 0 | None |
| 0.0 | 5.0 | 315 | 10.8619 | 0.0245 | 0 | 0 | None |
| 0.0 | 6.0 | 378 | 11.2608 | 0.0165 | 0 | 0 | None |
| 0.0 | 7.0 | 441 | 11.9442 | 0.0132 | 0 | 0 | None |
| 0.0 | 8.0 | 504 | 12.2665 | 0.0127 | 0 | 0 | None |
| 0.0 | 9.0 | 567 | 12.7264 | 0.0135 | 0 | 0 | None |
| 0.0 | 10.0 | 630 | 12.1434 | 0.0125 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.15.2