100
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: -8.0584
- Accuracy: 0.2183
- Dt Accuracy: 0.2183
- Df Accuracy: 0.2247
- 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: 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 | 24 | -0.1489 | 0.9693 | 0.2308 | 0.2308 | None |
| No log | 2.0 | 48 | -0.4945 | 0.8987 | 0.3300 | 0.3300 | None |
| No log | 3.0 | 72 | -1.4536 | 0.7517 | 0.4815 | 0.4815 | None |
| No log | 4.0 | 96 | -2.8098 | 0.5773 | 0 | 0 | None |
| No log | 5.0 | 120 | -4.4581 | 0.4247 | 0 | 0 | None |
| No log | 6.0 | 144 | -5.8964 | 0.3307 | 0 | 0 | None |
| No log | 7.0 | 168 | -6.9167 | 0.274 | 0 | 0 | None |
| No log | 8.0 | 192 | -7.6241 | 0.2473 | 0 | 0 | None |
| No log | 9.0 | 216 | -7.9234 | 0.2293 | 0 | 0 | None |
| No log | 10.0 | 240 | -8.0584 | 0.2247 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2