13
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: -11.0264
- Accuracy: 0.0837
- Dt Accuracy: 0.0837
- Df Accuracy: 0.087
- 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: 13
- 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 | 32 | -0.1638 | 0.9665 | 0.2350 | 0.2350 | None |
| No log | 2.0 | 64 | -0.7806 | 0.8245 | 0.4152 | 0.4152 | None |
| No log | 3.0 | 96 | -2.4212 | 0.5677 | 0 | 0 | None |
| No log | 4.0 | 128 | -4.0318 | 0.3775 | 0 | 0 | None |
| No log | 5.0 | 160 | -5.7104 | 0.2333 | 0 | 0 | None |
| No log | 6.0 | 192 | -7.7014 | 0.1557 | 0 | 0 | None |
| No log | 7.0 | 224 | -9.2223 | 0.1153 | 0 | 0 | None |
| No log | 8.0 | 256 | -10.4204 | 0.0948 | 0 | 0 | None |
| No log | 9.0 | 288 | -10.9499 | 0.089 | 0 | 0 | None |
| No log | 10.0 | 320 | -11.0264 | 0.087 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2