42
This model is a fine-tuned version of microsoft/resnet-34 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: -6.0399
- Accuracy: 0.4378
- Dt Accuracy: 0.4378
- Df Accuracy: 0.432
- 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 | 8 | -0.2120 | 0.964 | 0.2387 | 0.2387 | None |
| No log | 2.0 | 16 | -0.7569 | 0.862 | 0.3750 | 0.3750 | None |
| No log | 3.0 | 24 | -1.9209 | 0.748 | 0.4841 | 0.4841 | None |
| No log | 4.0 | 32 | -3.1610 | 0.611 | 0.5587 | 0.5587 | None |
| No log | 5.0 | 40 | -4.2972 | 0.503 | 0 | 0 | None |
| No log | 6.0 | 48 | -5.2161 | 0.46 | 0 | 0 | None |
| No log | 7.0 | 56 | -5.7034 | 0.441 | 0 | 0 | None |
| No log | 8.0 | 64 | -5.9644 | 0.435 | 0 | 0 | None |
| No log | 9.0 | 72 | -6.0803 | 0.433 | 0 | 0 | None |
| No log | 10.0 | 80 | -6.0399 | 0.432 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2