21
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: -9.3150
- Accuracy: 0.1346
- Dt Accuracy: 0.1346
- Df Accuracy: 0.1337
- 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: 21
- 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 | 24 | -0.6560 | 0.859 | 0.2613 | 0.2613 | None |
| No log | 2.0 | 48 | -1.1345 | 0.741 | 0.4113 | 0.4113 | None |
| No log | 3.0 | 72 | -2.3057 | 0.574 | 0.5473 | 0.5473 | None |
| No log | 4.0 | 96 | -4.0565 | 0.426 | 0 | 0 | None |
| -2.3782 | 5.0 | 120 | -5.7368 | 0.318 | 0 | 0 | None |
| -2.3782 | 6.0 | 144 | -7.3533 | 0.2363 | 0 | 0 | None |
| -2.3782 | 7.0 | 168 | -8.4022 | 0.1873 | 0 | 0 | None |
| -2.3782 | 8.0 | 192 | -9.1579 | 0.1557 | 0 | 0 | None |
| -8.784 | 9.0 | 216 | -9.3536 | 0.138 | 0 | 0 | None |
| -8.784 | 10.0 | 240 | -9.3150 | 0.1337 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.15.2