21
This model is a fine-tuned version of microsoft/resnet-50 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: -14.1204
- Accuracy: 0.1458
- Dt Accuracy: 0.1458
- Df Accuracy: 0.1422
- 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 | 40 | -0.1840 | 0.9608 | 0.2438 | 0.2438 | None |
| No log | 2.0 | 80 | -1.6858 | 0.651 | 0.5409 | 0.5409 | None |
| No log | 3.0 | 120 | -4.8486 | 0.3424 | 0 | 0 | None |
| No log | 4.0 | 160 | -7.2107 | 0.2354 | 0 | 0 | None |
| No log | 5.0 | 200 | -8.9823 | 0.194 | 0 | 0 | None |
| No log | 6.0 | 240 | -10.8622 | 0.17 | 0 | 0 | None |
| No log | 7.0 | 280 | -11.9466 | 0.1562 | 0 | 0 | None |
| No log | 8.0 | 320 | -13.3370 | 0.1488 | 0 | 0 | None |
| No log | 9.0 | 360 | -13.9369 | 0.1438 | 0 | 0 | None |
| No log | 10.0 | 400 | -14.1204 | 0.1422 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2