42
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: -4.4300
- Accuracy: 0.3471
- Dt Accuracy: 0.3471
- Df Accuracy: 0.348
- 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 | 16 | -0.5995 | 0.881 | 0.2282 | 0.2282 | None |
| No log | 2.0 | 32 | -0.7574 | 0.814 | 0.3247 | 0.3247 | None |
| No log | 3.0 | 48 | -1.0902 | 0.7205 | 0.4349 | 0.4349 | None |
| No log | 4.0 | 64 | -1.6381 | 0.637 | 0.5060 | 0.5060 | None |
| No log | 5.0 | 80 | -2.3115 | 0.5525 | 0.5532 | 0.5532 | None |
| No log | 6.0 | 96 | -2.9602 | 0.479 | 0 | 0 | None |
| -2.1949 | 7.0 | 112 | -3.6324 | 0.4075 | 0 | 0 | None |
| -2.1949 | 8.0 | 128 | -4.0724 | 0.3765 | 0 | 0 | None |
| -2.1949 | 9.0 | 144 | -4.3513 | 0.3535 | 0 | 0 | None |
| -2.1949 | 10.0 | 160 | -4.4300 | 0.348 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.15.2