swin-tiny-patch4-window7-224-ve-U11-b-80
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: 0.7088
- Accuracy: 0.7826
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: 80
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.92 | 6 | 1.3860 | 0.1304 |
| 1.3859 | 2.0 | 13 | 1.3832 | 0.2609 |
| 1.3859 | 2.92 | 19 | 1.3773 | 0.2609 |
| 1.3791 | 4.0 | 26 | 1.3569 | 0.2174 |
| 1.3347 | 4.92 | 32 | 1.3177 | 0.2609 |
| 1.3347 | 6.0 | 39 | 1.2093 | 0.3913 |
| 1.2088 | 6.92 | 45 | 1.1083 | 0.4348 |
| 1.0456 | 8.0 | 52 | 1.0340 | 0.4565 |
| 1.0456 | 8.92 | 58 | 1.0120 | 0.5 |
| 0.9278 | 10.0 | 65 | 0.9282 | 0.5652 |
| 0.847 | 10.92 | 71 | 0.9934 | 0.5217 |
| 0.847 | 12.0 | 78 | 1.0171 | 0.4783 |
| 0.7142 | 12.92 | 84 | 0.8889 | 0.5870 |
| 0.5959 | 14.0 | 91 | 0.9392 | 0.5870 |
| 0.5959 | 14.92 | 97 | 0.9018 | 0.6304 |
| 0.5344 | 16.0 | 104 | 0.8327 | 0.6739 |
| 0.4438 | 16.92 | 110 | 0.7308 | 0.7391 |
| 0.4438 | 18.0 | 117 | 0.6834 | 0.7174 |
| 0.4419 | 18.92 | 123 | 0.7909 | 0.6304 |
| 0.3989 | 20.0 | 130 | 0.9103 | 0.6739 |
| 0.3989 | 20.92 | 136 | 0.7534 | 0.7391 |
| 0.3534 | 22.0 | 143 | 0.8043 | 0.7391 |
| 0.3534 | 22.92 | 149 | 0.7648 | 0.7174 |
| 0.3265 | 24.0 | 156 | 0.7088 | 0.7826 |
| 0.2808 | 24.92 | 162 | 0.8845 | 0.6957 |
| 0.2808 | 26.0 | 169 | 0.7756 | 0.7609 |
| 0.2753 | 26.92 | 175 | 0.9944 | 0.6087 |
| 0.2837 | 28.0 | 182 | 0.8091 | 0.7174 |
| 0.2837 | 28.92 | 188 | 0.9966 | 0.6739 |
| 0.2667 | 30.0 | 195 | 0.7711 | 0.7826 |
| 0.2325 | 30.92 | 201 | 0.8946 | 0.6957 |
| 0.2325 | 32.0 | 208 | 0.9079 | 0.6739 |
| 0.2096 | 32.92 | 214 | 1.0338 | 0.6522 |
| 0.1733 | 34.0 | 221 | 0.8191 | 0.7391 |
| 0.1733 | 34.92 | 227 | 1.0068 | 0.6957 |
| 0.1975 | 36.0 | 234 | 0.8644 | 0.7174 |
| 0.1844 | 36.92 | 240 | 0.8682 | 0.6739 |
| 0.1844 | 38.0 | 247 | 0.7915 | 0.7609 |
| 0.1701 | 38.92 | 253 | 0.7554 | 0.7609 |
| 0.1696 | 40.0 | 260 | 0.8762 | 0.7174 |
| 0.1696 | 40.92 | 266 | 1.0173 | 0.6739 |
| 0.1556 | 42.0 | 273 | 0.9080 | 0.7174 |
| 0.1556 | 42.92 | 279 | 1.2456 | 0.6739 |
| 0.153 | 44.0 | 286 | 0.9820 | 0.7391 |
| 0.1343 | 44.92 | 292 | 0.9908 | 0.7174 |
| 0.1343 | 46.0 | 299 | 0.9435 | 0.7391 |
| 0.1513 | 46.92 | 305 | 0.8842 | 0.7826 |
| 0.1402 | 48.0 | 312 | 1.0207 | 0.6739 |
| 0.1402 | 48.92 | 318 | 0.9915 | 0.7174 |
| 0.1648 | 50.0 | 325 | 1.1576 | 0.6739 |
| 0.1047 | 50.92 | 331 | 1.2283 | 0.6739 |
| 0.1047 | 52.0 | 338 | 1.0869 | 0.6957 |
| 0.1223 | 52.92 | 344 | 1.1203 | 0.7174 |
| 0.1223 | 54.0 | 351 | 0.9685 | 0.7174 |
| 0.1223 | 54.92 | 357 | 1.1926 | 0.7174 |
| 0.1236 | 56.0 | 364 | 1.0088 | 0.7174 |
| 0.1115 | 56.92 | 370 | 0.9149 | 0.7391 |
| 0.1115 | 58.0 | 377 | 0.8820 | 0.7391 |
| 0.1173 | 58.92 | 383 | 0.9653 | 0.7391 |
| 0.102 | 60.0 | 390 | 1.0046 | 0.7174 |
| 0.102 | 60.92 | 396 | 1.0585 | 0.6957 |
| 0.1206 | 62.0 | 403 | 1.0490 | 0.6957 |
| 0.1206 | 62.92 | 409 | 0.9683 | 0.7609 |
| 0.1124 | 64.0 | 416 | 0.9627 | 0.7609 |
| 0.0927 | 64.92 | 422 | 0.9771 | 0.7609 |
| 0.0927 | 66.0 | 429 | 1.0002 | 0.7174 |
| 0.0906 | 66.92 | 435 | 0.9607 | 0.7391 |
| 0.084 | 68.0 | 442 | 0.9414 | 0.7391 |
| 0.084 | 68.92 | 448 | 0.9863 | 0.7174 |
| 0.0866 | 70.0 | 455 | 0.9930 | 0.7174 |
| 0.0944 | 70.92 | 461 | 0.9981 | 0.7174 |
| 0.0944 | 72.0 | 468 | 1.0039 | 0.7174 |
| 0.1064 | 72.92 | 474 | 0.9987 | 0.7174 |
| 0.1074 | 73.85 | 480 | 0.9964 | 0.7174 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0