100
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: 7.1769
- Accuracy: 0.1352
- Dt Accuracy: 0.1352
- Df Accuracy: 0.1285
- 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: 100
- 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 | 0.9325 | 0.8225 | 0.3117 | 0.3117 | None |
| No log | 2.0 | 64 | 1.7361 | 0.6495 | 0 | 0 | None |
| No log | 3.0 | 96 | 2.2903 | 0.537 | 0 | 0 | None |
| 0.0 | 4.0 | 128 | 3.6689 | 0.385 | 0 | 0 | None |
| 0.0 | 5.0 | 160 | 5.2126 | 0.285 | 0 | 0 | None |
| 0.0 | 6.0 | 192 | 4.8897 | 0.2345 | 0 | 0 | None |
| 0.0 | 7.0 | 224 | 6.8840 | 0.1645 | 0 | 0 | None |
| 0.0 | 8.0 | 256 | 6.8209 | 0.147 | 0 | 0 | None |
| 0.0 | 9.0 | 288 | 7.8211 | 0.131 | 0 | 0 | None |
| 0.0 | 10.0 | 320 | 7.1769 | 0.1285 | 0 | 0 | None |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.15.2