42
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: -15.5756
- Accuracy: 0.0845
- Dt Accuracy: 0.0845
- Df Accuracy: 0.0866
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 40 | -0.3082 | 0.9356 | 0.2804 | 0.2804 | None |
| No log | 2.0 | 80 | -1.7552 | 0.7372 | 0.4918 | 0.4918 | None |
| No log | 3.0 | 120 | -3.7635 | 0.5058 | 0 | 0 | None |
| No log | 4.0 | 160 | -6.2137 | 0.2284 | 0 | 0 | None |
| No log | 5.0 | 200 | -8.9372 | 0.1328 | 0 | 0 | None |
| No log | 6.0 | 240 | -10.8910 | 0.1098 | 0 | 0 | None |
| No log | 7.0 | 280 | -12.8848 | 0.096 | 0 | 0 | None |
| No log | 8.0 | 320 | -14.1557 | 0.09 | 0 | 0 | None |
| No log | 9.0 | 360 | -14.9199 | 0.0844 | 0 | 0 | None |
| No log | 10.0 | 400 | -15.5756 | 0.0866 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2