metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SWIN-AI-Image-Detector
results: []
SWIN-AI-Image-Detector
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on CIFAKE dataset. It achieves the following results on the evaluation set:
- Loss: 0.0342
- Accuracy: 0.9874
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2432 | 1.0 | 703 | 0.1859 | 0.9267 |
0.1665 | 2.0 | 1406 | 0.1229 | 0.9514 |
0.1427 | 3.0 | 2109 | 0.0604 | 0.9761 |
0.143 | 4.0 | 2813 | 0.0807 | 0.97 |
0.1008 | 5.0 | 3516 | 0.0444 | 0.9824 |
0.1189 | 6.0 | 4219 | 0.0635 | 0.977 |
0.0936 | 7.0 | 4922 | 0.0535 | 0.9789 |
0.1201 | 8.0 | 5626 | 0.0376 | 0.9854 |
0.076 | 9.0 | 6329 | 0.0342 | 0.9874 |
0.0887 | 10.0 | 7030 | 0.0413 | 0.9844 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3