rt-detr-britain-handbooks-photos
This model is a fine-tuned version of PekingU/rtdetr_r50vd on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.9066
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 90
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 9 | 370.5898 |
| 542.4309 | 2.0 | 18 | 371.3819 |
| 522.3717 | 3.0 | 27 | 337.3348 |
| 459.2125 | 4.0 | 36 | 287.6073 |
| 395.5238 | 5.0 | 45 | 230.7955 |
| 286.8508 | 6.0 | 54 | 176.7677 |
| 228.066 | 7.0 | 63 | 136.6897 |
| 161.5375 | 8.0 | 72 | 99.1186 |
| 117.6188 | 9.0 | 81 | 78.7769 |
| 91.4598 | 10.0 | 90 | 60.9189 |
| 91.4598 | 11.0 | 99 | 48.0892 |
| 74.3667 | 12.0 | 108 | 41.1282 |
| 62.515 | 13.0 | 117 | 34.5201 |
| 52.9375 | 14.0 | 126 | 32.2538 |
| 44.9663 | 15.0 | 135 | 29.8093 |
| 40.1683 | 16.0 | 144 | 26.0296 |
| 36.8552 | 17.0 | 153 | 25.6356 |
| 31.1489 | 18.0 | 162 | 20.8665 |
| 28.862 | 19.0 | 171 | 18.5289 |
| 26.1241 | 20.0 | 180 | 16.8950 |
| 26.1241 | 21.0 | 189 | 16.1161 |
| 23.8333 | 22.0 | 198 | 16.3788 |
| 20.779 | 23.0 | 207 | 14.8389 |
| 19.1705 | 24.0 | 216 | 13.2360 |
| 18.1938 | 25.0 | 225 | 12.2007 |
| 16.0306 | 26.0 | 234 | 11.2442 |
| 15.0287 | 27.0 | 243 | 10.4789 |
| 14.8518 | 28.0 | 252 | 9.8145 |
| 13.2291 | 29.0 | 261 | 9.2670 |
| 12.8187 | 30.0 | 270 | 9.0118 |
| 12.8187 | 31.0 | 279 | 8.4731 |
| 11.8135 | 32.0 | 288 | 7.8816 |
| 11.8473 | 33.0 | 297 | 7.9214 |
| 10.3618 | 34.0 | 306 | 7.2866 |
| 11.291 | 35.0 | 315 | 6.7351 |
| 9.5297 | 36.0 | 324 | 6.5649 |
| 9.1887 | 37.0 | 333 | 6.3402 |
| 9.3662 | 38.0 | 342 | 6.8995 |
| 8.8807 | 39.0 | 351 | 6.7314 |
| 8.871 | 40.0 | 360 | 6.3205 |
| 8.871 | 41.0 | 369 | 6.2681 |
| 8.4285 | 42.0 | 378 | 6.1505 |
| 8.0272 | 43.0 | 387 | 5.7252 |
| 7.7106 | 44.0 | 396 | 5.7598 |
| 7.6973 | 45.0 | 405 | 5.8607 |
| 7.4816 | 46.0 | 414 | 5.8354 |
| 7.7731 | 47.0 | 423 | 6.1469 |
| 7.3577 | 48.0 | 432 | 5.7994 |
| 6.9262 | 49.0 | 441 | 5.7957 |
| 6.7817 | 50.0 | 450 | 5.3749 |
| 6.7817 | 51.0 | 459 | 5.4785 |
| 6.4421 | 52.0 | 468 | 5.5997 |
| 6.6866 | 53.0 | 477 | 5.6428 |
| 6.2332 | 54.0 | 486 | 5.2460 |
| 6.033 | 55.0 | 495 | 5.0726 |
| 6.4574 | 56.0 | 504 | 5.0716 |
| 5.8004 | 57.0 | 513 | 5.1538 |
| 6.3994 | 58.0 | 522 | 5.2739 |
| 5.4569 | 59.0 | 531 | 4.9320 |
| 6.8395 | 60.0 | 540 | 4.8320 |
| 6.8395 | 61.0 | 549 | 4.8788 |
| 5.6847 | 62.0 | 558 | 5.0752 |
| 6.0732 | 63.0 | 567 | 5.1419 |
| 5.5805 | 64.0 | 576 | 5.0951 |
| 5.5178 | 65.0 | 585 | 5.1321 |
| 5.1452 | 66.0 | 594 | 4.9179 |
| 5.4156 | 67.0 | 603 | 4.9118 |
| 5.5653 | 68.0 | 612 | 4.9279 |
| 5.2236 | 69.0 | 621 | 4.8551 |
| 5.3366 | 70.0 | 630 | 5.1762 |
| 5.3366 | 71.0 | 639 | 4.9683 |
| 5.2791 | 72.0 | 648 | 5.0238 |
| 5.5227 | 73.0 | 657 | 4.9368 |
| 4.9659 | 74.0 | 666 | 4.9490 |
| 5.1077 | 75.0 | 675 | 4.9549 |
| 5.1386 | 76.0 | 684 | 4.9591 |
| 5.2915 | 77.0 | 693 | 4.9849 |
| 4.9752 | 78.0 | 702 | 5.1533 |
| 5.2248 | 79.0 | 711 | 4.9699 |
| 5.2362 | 80.0 | 720 | 5.0121 |
| 5.2362 | 81.0 | 729 | 4.9954 |
| 5.1962 | 82.0 | 738 | 5.0266 |
| 4.9936 | 83.0 | 747 | 4.9814 |
| 4.9174 | 84.0 | 756 | 5.0074 |
| 5.1872 | 85.0 | 765 | 5.2822 |
| 5.3053 | 86.0 | 774 | 4.9256 |
| 4.7016 | 87.0 | 783 | 4.9502 |
| 5.1849 | 88.0 | 792 | 5.0745 |
| 5.2689 | 89.0 | 801 | 5.0272 |
| 4.9275 | 90.0 | 810 | 4.9066 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1