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: 5.5316
- Accuracy: 0.6966
- Dt Accuracy: 0.6966
- Df Accuracy: 0.703
- 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 | 47 | 2.1024 | 0.8077 | 0.4324 | 0.4324 | None |
| No log | 2.0 | 94 | 3.6595 | 0.7637 | 0 | 0 | None |
| No log | 3.0 | 141 | 4.1023 | 0.745 | 0 | 0 | None |
| No log | 4.0 | 188 | 4.6068 | 0.7287 | 0 | 0 | None |
| No log | 5.0 | 235 | 4.5776 | 0.7303 | 0 | 0 | None |
| No log | 6.0 | 282 | 5.1808 | 0.717 | 0 | 0 | None |
| No log | 7.0 | 329 | 5.3526 | 0.6953 | 0 | 0 | None |
| No log | 8.0 | 376 | 5.7350 | 0.7077 | 0 | 0 | None |
| No log | 9.0 | 423 | 5.3134 | 0.7147 | 0 | 0 | None |
| No log | 10.0 | 470 | 5.5316 | 0.703 | 0 | 0 | None |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2