cards-top_left_swin-tiny-patch4-window7-224-finetuned-v3_more_data
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.9722
- Accuracy: 0.5941
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5501 | 1.0 | 1346 | 1.2633 | 0.4645 |
| 1.4882 | 2.0 | 2692 | 1.1866 | 0.4951 |
| 1.5148 | 3.0 | 4038 | 1.1644 | 0.5066 |
| 1.4605 | 4.0 | 5384 | 1.1546 | 0.5105 |
| 1.425 | 5.0 | 6730 | 1.0940 | 0.5361 |
| 1.4452 | 6.0 | 8076 | 1.0750 | 0.5530 |
| 1.4507 | 7.0 | 9422 | 1.0997 | 0.5301 |
| 1.4435 | 8.0 | 10768 | 1.0835 | 0.5445 |
| 1.3904 | 9.0 | 12114 | 1.0587 | 0.5493 |
| 1.3826 | 10.0 | 13460 | 1.0434 | 0.5581 |
| 1.4186 | 11.0 | 14806 | 1.0515 | 0.5536 |
| 1.3938 | 12.0 | 16152 | 1.0283 | 0.5635 |
| 1.3763 | 13.0 | 17498 | 1.0140 | 0.5740 |
| 1.3873 | 14.0 | 18844 | 1.0557 | 0.5470 |
| 1.3833 | 15.0 | 20190 | 1.0244 | 0.5638 |
| 1.385 | 16.0 | 21536 | 1.0345 | 0.5584 |
| 1.3492 | 17.0 | 22882 | 0.9997 | 0.5757 |
| 1.3332 | 18.0 | 24228 | 1.0106 | 0.5697 |
| 1.399 | 19.0 | 25574 | 0.9867 | 0.5846 |
| 1.3117 | 20.0 | 26920 | 0.9929 | 0.5833 |
| 1.362 | 21.0 | 28266 | 0.9895 | 0.5861 |
| 1.3279 | 22.0 | 29612 | 0.9853 | 0.5858 |
| 1.3057 | 23.0 | 30958 | 0.9872 | 0.5865 |
| 1.3217 | 24.0 | 32304 | 0.9761 | 0.5909 |
| 1.2854 | 25.0 | 33650 | 0.9800 | 0.5910 |
| 1.3194 | 26.0 | 34996 | 0.9867 | 0.5901 |
| 1.2733 | 27.0 | 36342 | 0.9927 | 0.5871 |
| 1.2949 | 28.0 | 37688 | 0.9755 | 0.5939 |
| 1.2836 | 29.0 | 39034 | 0.9738 | 0.5940 |
| 1.2974 | 30.0 | 40380 | 0.9722 | 0.5941 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2