87
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: 6.8180
- Accuracy: 0.6917
- Dt Accuracy: 0.6917
- Df Accuracy: 0.6943
- 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- seed: 87
- 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 | 63 | 2.4957 | 0.796 | 0.4435 | 0.4435 | None |
| No log | 2.0 | 126 | 4.5726 | 0.7432 | 0 | 0 | None |
| No log | 3.0 | 189 | 6.4544 | 0.6947 | 0 | 0 | None |
| No log | 4.0 | 252 | 7.2136 | 0.6947 | 0 | 0 | None |
| No log | 5.0 | 315 | 6.5031 | 0.702 | 0 | 0 | None |
| No log | 6.0 | 378 | 5.9597 | 0.6975 | 0 | 0 | None |
| No log | 7.0 | 441 | 7.0755 | 0.6775 | 0 | 0 | None |
| 0.0 | 8.0 | 504 | 6.6842 | 0.6917 | 0 | 0 | None |
| 0.0 | 9.0 | 567 | 7.2451 | 0.7017 | 0 | 0 | None |
| 0.0 | 10.0 | 630 | 6.8180 | 0.6943 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2