Hugging Face's logo

mfly-auton
/
suas-2025-rtdetr-finetuned-e20-b16-lr1e-5

Object Detection
Transformers
Safetensors
rt_detr
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
emvisee commited on
Commit
464c8d2
•
1 Parent(s): 66bf022

Model save

Browse files
Files changed (5) hide show
  1. README.md +120 -0
  2. config.json +125 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +29 -0
  5. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,120 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ base_model: PekingU/rtdetr_r50vd
5
+ tags:
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: suas-2025-rtdetr-finetuned-e20-b16-lr1e-5
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # suas-2025-rtdetr-finetuned-e20-b16-lr1e-5
16
+
17
+ This model is a fine-tuned version of [PekingU/rtdetr_r50vd](https://huggingface.co/PekingU/rtdetr_r50vd) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 5.3994
20
+ - Map: 0.7432
21
+ - Map 50: 0.826
22
+ - Map 75: 0.8194
23
+ - Map Small: 0.6733
24
+ - Map Medium: 0.7514
25
+ - Map Large: 0.8478
26
+ - Mar 1: 0.7418
27
+ - Mar 10: 0.8747
28
+ - Mar 100: 0.8873
29
+ - Mar Small: 0.7457
30
+ - Mar Medium: 0.9276
31
+ - Mar Large: 0.9725
32
+ - Map Baseball-bat: 0.8321
33
+ - Mar 100 Baseball-bat: 0.8874
34
+ - Map Basketball: 0.5876
35
+ - Mar 100 Basketball: 0.6948
36
+ - Map Car: -1.0
37
+ - Mar 100 Car: -1.0
38
+ - Map Football: 0.7601
39
+ - Mar 100 Football: 0.8239
40
+ - Map Human: 0.3724
41
+ - Mar 100 Human: 0.8567
42
+ - Map Luggage: 0.3313
43
+ - Mar 100 Luggage: 0.933
44
+ - Map Mattress: 0.9551
45
+ - Mar 100 Mattress: 0.9933
46
+ - Map Motorcycle: 0.9352
47
+ - Mar 100 Motorcycle: 0.9758
48
+ - Map Skis: 0.9499
49
+ - Mar 100 Skis: 0.9861
50
+ - Map Snowboard: 0.7494
51
+ - Mar 100 Snowboard: 0.9924
52
+ - Map Soccer-ball: 0.6994
53
+ - Mar 100 Soccer-ball: 0.7859
54
+ - Map Stop-sign: 0.9566
55
+ - Mar 100 Stop-sign: 0.9908
56
+ - Map Tennis-racket: 0.8019
57
+ - Mar 100 Tennis-racket: 0.8663
58
+ - Map Umbrella: 0.8881
59
+ - Mar 100 Umbrella: 0.926
60
+ - Map Volleyball: 0.5851
61
+ - Mar 100 Volleyball: 0.71
62
+
63
+ ## Model description
64
+
65
+ More information needed
66
+
67
+ ## Intended uses & limitations
68
+
69
+ More information needed
70
+
71
+ ## Training and evaluation data
72
+
73
+ More information needed
74
+
75
+ ## Training procedure
76
+
77
+ ### Training hyperparameters
78
+
79
+ The following hyperparameters were used during training:
80
+ - learning_rate: 1e-05
81
+ - train_batch_size: 16
82
+ - eval_batch_size: 32
83
+ - seed: 1337
84
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
85
+ - lr_scheduler_type: linear
86
+ - num_epochs: 20.0
87
+ - mixed_precision_training: Native AMP
88
+
89
+ ### Training results
90
+
91
+ | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Baseball-bat | Mar 100 Baseball-bat | Map Basketball | Mar 100 Basketball | Map Car | Mar 100 Car | Map Football | Mar 100 Football | Map Human | Mar 100 Human | Map Luggage | Mar 100 Luggage | Map Mattress | Mar 100 Mattress | Map Motorcycle | Mar 100 Motorcycle | Map Skis | Mar 100 Skis | Map Snowboard | Mar 100 Snowboard | Map Soccer-ball | Mar 100 Soccer-ball | Map Stop-sign | Mar 100 Stop-sign | Map Tennis-racket | Mar 100 Tennis-racket | Map Umbrella | Mar 100 Umbrella | Map Volleyball | Mar 100 Volleyball |
92
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------------:|:--------------------:|:--------------:|:------------------:|:-------:|:-----------:|:------------:|:----------------:|:---------:|:-------------:|:-----------:|:---------------:|:------------:|:----------------:|:--------------:|:------------------:|:--------:|:------------:|:-------------:|:-----------------:|:---------------:|:-------------------:|:-------------:|:-----------------:|:-----------------:|:---------------------:|:------------:|:----------------:|:--------------:|:------------------:|
93
+ | 31.215 | 1.0 | 438 | 11.5331 | 0.361 | 0.4429 | 0.3939 | 0.2412 | 0.3572 | 0.4631 | 0.5413 | 0.7216 | 0.7456 | 0.4705 | 0.8339 | 0.9133 | 0.5278 | 0.7534 | 0.201 | 0.5637 | -1.0 | -1.0 | 0.0954 | 0.3392 | 0.2978 | 0.8908 | 0.2173 | 0.8347 | 0.9008 | 0.9776 | 0.2558 | 0.8724 | 0.3715 | 0.9332 | 0.476 | 0.9786 | 0.1347 | 0.3499 | 0.4095 | 0.8757 | 0.2533 | 0.7259 | 0.5596 | 0.7477 | 0.3531 | 0.5963 |
94
+ | 11.6728 | 2.0 | 876 | 8.1149 | 0.6758 | 0.7641 | 0.7545 | 0.57 | 0.7049 | 0.7078 | 0.7463 | 0.8668 | 0.8748 | 0.7153 | 0.9205 | 0.9633 | 0.7816 | 0.8531 | 0.5697 | 0.7246 | -1.0 | -1.0 | 0.345 | 0.6959 | 0.4186 | 0.9573 | 0.4077 | 0.9314 | 0.9689 | 0.994 | 0.8579 | 0.9524 | 0.8735 | 0.9856 | 0.532 | 0.9963 | 0.6632 | 0.7347 | 0.8767 | 0.9606 | 0.7409 | 0.8627 | 0.7848 | 0.8651 | 0.641 | 0.7331 |
95
+ | 8.5279 | 3.0 | 1314 | 7.1741 | 0.7245 | 0.8123 | 0.8048 | 0.6062 | 0.7523 | 0.777 | 0.7631 | 0.8836 | 0.89 | 0.7351 | 0.9328 | 0.9734 | 0.8031 | 0.8681 | 0.6326 | 0.7732 | -1.0 | -1.0 | 0.4741 | 0.7704 | 0.4663 | 0.9645 | 0.575 | 0.9431 | 0.9754 | 0.999 | 0.8934 | 0.9659 | 0.9026 | 0.9886 | 0.6149 | 0.9966 | 0.6406 | 0.7162 | 0.9225 | 0.9712 | 0.7727 | 0.871 | 0.8448 | 0.9059 | 0.6252 | 0.7262 |
96
+ | 7.6535 | 4.0 | 1752 | 6.6320 | 0.7374 | 0.8206 | 0.8145 | 0.6387 | 0.7807 | 0.8649 | 0.7702 | 0.8941 | 0.9 | 0.7649 | 0.9395 | 0.9869 | 0.7844 | 0.8691 | 0.6492 | 0.7808 | -1.0 | -1.0 | 0.5894 | 0.7994 | 0.5001 | 0.9605 | 0.6277 | 0.9445 | 0.9591 | 0.9887 | 0.8951 | 0.9695 | 0.9208 | 0.9916 | 0.6658 | 0.9969 | 0.6457 | 0.753 | 0.9478 | 0.9911 | 0.6932 | 0.8881 | 0.8172 | 0.9059 | 0.6283 | 0.7608 |
97
+ | 7.2488 | 5.0 | 2190 | 6.2374 | 0.7287 | 0.8175 | 0.8097 | 0.6049 | 0.7712 | 0.8579 | 0.7514 | 0.88 | 0.8863 | 0.7218 | 0.936 | 0.9754 | 0.7896 | 0.8726 | 0.5603 | 0.7192 | -1.0 | -1.0 | 0.5343 | 0.7579 | 0.4718 | 0.9494 | 0.587 | 0.9343 | 0.9709 | 0.9983 | 0.9089 | 0.9678 | 0.9366 | 0.9871 | 0.6894 | 0.994 | 0.6338 | 0.7283 | 0.9115 | 0.9824 | 0.7501 | 0.8819 | 0.8789 | 0.9342 | 0.5784 | 0.7002 |
98
+ | 6.8555 | 6.0 | 2628 | 5.8678 | 0.7433 | 0.827 | 0.8208 | 0.6423 | 0.7801 | 0.8658 | 0.7602 | 0.8885 | 0.8951 | 0.7482 | 0.9368 | 0.9758 | 0.7919 | 0.8791 | 0.5608 | 0.7367 | -1.0 | -1.0 | 0.615 | 0.7904 | 0.4469 | 0.9424 | 0.5827 | 0.9428 | 0.9483 | 0.9862 | 0.9122 | 0.9755 | 0.9423 | 0.9871 | 0.7175 | 0.9961 | 0.6653 | 0.7622 | 0.9489 | 0.9858 | 0.7588 | 0.8912 | 0.8966 | 0.9336 | 0.6192 | 0.7221 |
99
+ | 6.5361 | 7.0 | 3066 | 5.9374 | 0.734 | 0.8181 | 0.8106 | 0.6512 | 0.7467 | 0.8574 | 0.7529 | 0.8832 | 0.8931 | 0.7511 | 0.9359 | 0.9841 | 0.8065 | 0.872 | 0.6151 | 0.7562 | -1.0 | -1.0 | 0.6614 | 0.7874 | 0.4174 | 0.9248 | 0.4939 | 0.9356 | 0.942 | 0.9844 | 0.8818 | 0.9698 | 0.9076 | 0.9861 | 0.671 | 0.9917 | 0.6563 | 0.7728 | 0.9323 | 0.983 | 0.7992 | 0.8741 | 0.8936 | 0.9344 | 0.5979 | 0.7309 |
100
+ | 6.4654 | 8.0 | 3504 | 5.7246 | 0.7424 | 0.8246 | 0.8179 | 0.6646 | 0.7573 | 0.8599 | 0.7499 | 0.8842 | 0.8929 | 0.7598 | 0.9351 | 0.978 | 0.8053 | 0.8782 | 0.6157 | 0.7374 | -1.0 | -1.0 | 0.7003 | 0.806 | 0.4102 | 0.8962 | 0.4673 | 0.9298 | 0.9592 | 0.996 | 0.9053 | 0.9757 | 0.9176 | 0.9832 | 0.6832 | 0.9929 | 0.6794 | 0.7789 | 0.9531 | 0.9841 | 0.7883 | 0.8767 | 0.9071 | 0.9426 | 0.6009 | 0.7235 |
101
+ | 6.2384 | 9.0 | 3942 | 5.6544 | 0.7571 | 0.8377 | 0.8316 | 0.6868 | 0.7743 | 0.8518 | 0.7582 | 0.8902 | 0.8996 | 0.768 | 0.938 | 0.9823 | 0.8088 | 0.8861 | 0.6286 | 0.7505 | -1.0 | -1.0 | 0.7342 | 0.8303 | 0.3974 | 0.9053 | 0.5417 | 0.9339 | 0.9387 | 0.9891 | 0.9022 | 0.9776 | 0.9246 | 0.9856 | 0.7247 | 0.9971 | 0.6929 | 0.7964 | 0.9621 | 0.9894 | 0.8007 | 0.8756 | 0.9151 | 0.9437 | 0.6276 | 0.7343 |
102
+ | 6.1353 | 10.0 | 4380 | 5.4540 | 0.7621 | 0.8461 | 0.8394 | 0.6938 | 0.7761 | 0.7476 | 0.7578 | 0.8899 | 0.8995 | 0.7695 | 0.937 | 0.9809 | 0.8248 | 0.8844 | 0.6711 | 0.7713 | -1.0 | -1.0 | 0.7385 | 0.8195 | 0.3992 | 0.9066 | 0.4718 | 0.9348 | 0.9559 | 0.9962 | 0.9208 | 0.9766 | 0.9513 | 0.9837 | 0.7604 | 0.994 | 0.7046 | 0.8044 | 0.9673 | 0.9863 | 0.7906 | 0.8793 | 0.9127 | 0.9436 | 0.6007 | 0.7125 |
103
+ | 5.974 | 11.0 | 4818 | 5.4390 | 0.7477 | 0.8349 | 0.8284 | 0.6753 | 0.7641 | 0.7638 | 0.7469 | 0.8857 | 0.8944 | 0.7475 | 0.93 | 0.9817 | 0.8147 | 0.8746 | 0.5466 | 0.6886 | -1.0 | -1.0 | 0.7436 | 0.8223 | 0.404 | 0.9014 | 0.3508 | 0.9336 | 0.9558 | 0.9969 | 0.9219 | 0.9739 | 0.9454 | 0.9847 | 0.7481 | 0.9943 | 0.7203 | 0.8062 | 0.9647 | 0.9897 | 0.8395 | 0.899 | 0.9016 | 0.9352 | 0.6106 | 0.7216 |
104
+ | 5.8663 | 12.0 | 5256 | 5.5215 | 0.7399 | 0.8216 | 0.8156 | 0.6604 | 0.7621 | 0.7835 | 0.7392 | 0.8798 | 0.8907 | 0.7415 | 0.9304 | 0.9812 | 0.8193 | 0.8861 | 0.5166 | 0.6768 | -1.0 | -1.0 | 0.743 | 0.8184 | 0.3875 | 0.8986 | 0.3648 | 0.9283 | 0.9531 | 0.9957 | 0.9295 | 0.9768 | 0.9421 | 0.9851 | 0.737 | 0.9935 | 0.6957 | 0.7817 | 0.9635 | 0.9919 | 0.8015 | 0.8731 | 0.894 | 0.9316 | 0.6109 | 0.7319 |
105
+ | 5.7918 | 13.0 | 5694 | 5.3514 | 0.7531 | 0.8339 | 0.8294 | 0.6808 | 0.7732 | 0.7485 | 0.7501 | 0.8852 | 0.8945 | 0.7554 | 0.9306 | 0.9809 | 0.8172 | 0.8871 | 0.5405 | 0.6775 | -1.0 | -1.0 | 0.7592 | 0.8259 | 0.4135 | 0.8961 | 0.3898 | 0.9308 | 0.9633 | 0.9972 | 0.9278 | 0.9757 | 0.9412 | 0.9842 | 0.7532 | 0.9964 | 0.7259 | 0.8098 | 0.9708 | 0.993 | 0.8265 | 0.8881 | 0.8986 | 0.9342 | 0.6158 | 0.7272 |
106
+ | 5.6819 | 14.0 | 6132 | 5.3907 | 0.7409 | 0.8234 | 0.8192 | 0.6658 | 0.7677 | 0.8637 | 0.7392 | 0.8793 | 0.8897 | 0.7427 | 0.9314 | 0.9769 | 0.832 | 0.887 | 0.543 | 0.6746 | -1.0 | -1.0 | 0.7549 | 0.827 | 0.3854 | 0.8872 | 0.3596 | 0.9397 | 0.9524 | 0.9946 | 0.9291 | 0.9747 | 0.9396 | 0.9817 | 0.7553 | 0.9929 | 0.7004 | 0.7931 | 0.9573 | 0.9941 | 0.7972 | 0.8793 | 0.8857 | 0.917 | 0.5806 | 0.7127 |
107
+ | 5.6176 | 15.0 | 6570 | 5.3644 | 0.7503 | 0.8328 | 0.8268 | 0.687 | 0.7528 | 0.7741 | 0.7479 | 0.8838 | 0.8956 | 0.7622 | 0.9313 | 0.9754 | 0.8319 | 0.8887 | 0.5971 | 0.7175 | -1.0 | -1.0 | 0.7511 | 0.8231 | 0.3696 | 0.8842 | 0.3623 | 0.9325 | 0.9597 | 0.9982 | 0.933 | 0.9773 | 0.9431 | 0.9822 | 0.749 | 0.99 | 0.7222 | 0.8087 | 0.951 | 0.9891 | 0.8169 | 0.8772 | 0.8949 | 0.9306 | 0.6218 | 0.7392 |
108
+ | 5.5966 | 16.0 | 7008 | 5.3310 | 0.7507 | 0.8346 | 0.8279 | 0.6767 | 0.7694 | 0.8025 | 0.7483 | 0.8811 | 0.8923 | 0.7499 | 0.9334 | 0.977 | 0.8349 | 0.8921 | 0.5875 | 0.704 | -1.0 | -1.0 | 0.7511 | 0.8178 | 0.4005 | 0.8866 | 0.3754 | 0.9315 | 0.9489 | 0.995 | 0.929 | 0.9784 | 0.9487 | 0.9832 | 0.7675 | 0.9956 | 0.7136 | 0.799 | 0.9429 | 0.9905 | 0.8089 | 0.8668 | 0.903 | 0.936 | 0.5981 | 0.7159 |
109
+ | 5.6351 | 17.0 | 7446 | 5.4178 | 0.7425 | 0.8275 | 0.8194 | 0.6692 | 0.7577 | 0.8672 | 0.7429 | 0.874 | 0.8848 | 0.7397 | 0.9236 | 0.9722 | 0.8245 | 0.8846 | 0.5847 | 0.6853 | -1.0 | -1.0 | 0.7495 | 0.8156 | 0.3781 | 0.8625 | 0.3391 | 0.929 | 0.953 | 0.9962 | 0.9326 | 0.9754 | 0.9497 | 0.9847 | 0.7474 | 0.9914 | 0.7129 | 0.792 | 0.953 | 0.9894 | 0.8065 | 0.8674 | 0.8822 | 0.9149 | 0.5822 | 0.6988 |
110
+ | 5.5953 | 18.0 | 7884 | 5.4132 | 0.7431 | 0.8293 | 0.8213 | 0.6645 | 0.7644 | 0.854 | 0.7411 | 0.8735 | 0.8843 | 0.7377 | 0.9244 | 0.9736 | 0.8237 | 0.8832 | 0.5741 | 0.6656 | -1.0 | -1.0 | 0.7456 | 0.8154 | 0.374 | 0.8685 | 0.353 | 0.9315 | 0.9543 | 0.9966 | 0.9309 | 0.9768 | 0.9513 | 0.9847 | 0.7614 | 0.9916 | 0.6987 | 0.7805 | 0.9589 | 0.9888 | 0.8047 | 0.8596 | 0.8938 | 0.9276 | 0.5794 | 0.7096 |
111
+ | 5.5718 | 19.0 | 8322 | 5.3722 | 0.7427 | 0.8272 | 0.8194 | 0.6725 | 0.762 | 0.853 | 0.7405 | 0.8758 | 0.887 | 0.7438 | 0.9248 | 0.9745 | 0.836 | 0.8904 | 0.5708 | 0.6801 | -1.0 | -1.0 | 0.7528 | 0.8175 | 0.3645 | 0.8559 | 0.3216 | 0.9353 | 0.956 | 0.9962 | 0.9357 | 0.9766 | 0.9496 | 0.9866 | 0.7459 | 0.9934 | 0.7137 | 0.7949 | 0.9589 | 0.9919 | 0.8124 | 0.8684 | 0.8955 | 0.9267 | 0.5841 | 0.7042 |
112
+ | 5.5669 | 20.0 | 8760 | 5.3994 | 0.7432 | 0.826 | 0.8194 | 0.6733 | 0.7514 | 0.8478 | 0.7418 | 0.8747 | 0.8873 | 0.7457 | 0.9276 | 0.9725 | 0.8321 | 0.8874 | 0.5876 | 0.6948 | -1.0 | -1.0 | 0.7601 | 0.8239 | 0.3724 | 0.8567 | 0.3313 | 0.933 | 0.9551 | 0.9933 | 0.9352 | 0.9758 | 0.9499 | 0.9861 | 0.7494 | 0.9924 | 0.6994 | 0.7859 | 0.9566 | 0.9908 | 0.8019 | 0.8663 | 0.8881 | 0.926 | 0.5851 | 0.71 |
113
+
114
+
115
+ ### Framework versions
116
+
117
+ - Transformers 4.47.0
118
+ - Pytorch 2.5.1+cu124
119
+ - Datasets 3.1.0
120
+ - Tokenizers 0.21.0
config.json ADDED
@@ -0,0 +1,125 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "PekingU/rtdetr_r50vd",
3
+ "activation_dropout": 0.0,
4
+ "activation_function": "silu",
5
+ "anchor_image_size": null,
6
+ "architectures": [
7
+ "RTDetrForObjectDetection"
8
+ ],
9
+ "attention_dropout": 0.0,
10
+ "auxiliary_loss": true,
11
+ "backbone": null,
12
+ "backbone_config": {
13
+ "model_type": "rt_detr_resnet",
14
+ "out_features": [
15
+ "stage2",
16
+ "stage3",
17
+ "stage4"
18
+ ],
19
+ "out_indices": [
20
+ 2,
21
+ 3,
22
+ 4
23
+ ]
24
+ },
25
+ "backbone_kwargs": null,
26
+ "batch_norm_eps": 1e-05,
27
+ "box_noise_scale": 1.0,
28
+ "d_model": 256,
29
+ "decoder_activation_function": "relu",
30
+ "decoder_attention_heads": 8,
31
+ "decoder_ffn_dim": 1024,
32
+ "decoder_in_channels": [
33
+ 256,
34
+ 256,
35
+ 256
36
+ ],
37
+ "decoder_layers": 6,
38
+ "decoder_n_points": 4,
39
+ "disable_custom_kernels": true,
40
+ "dropout": 0.0,
41
+ "encode_proj_layers": [
42
+ 2
43
+ ],
44
+ "encoder_activation_function": "gelu",
45
+ "encoder_attention_heads": 8,
46
+ "encoder_ffn_dim": 1024,
47
+ "encoder_hidden_dim": 256,
48
+ "encoder_in_channels": [
49
+ 512,
50
+ 1024,
51
+ 2048
52
+ ],
53
+ "encoder_layers": 1,
54
+ "eos_coefficient": 0.0001,
55
+ "eval_size": null,
56
+ "feat_strides": [
57
+ 8,
58
+ 16,
59
+ 32
60
+ ],
61
+ "focal_loss_alpha": 0.75,
62
+ "focal_loss_gamma": 2.0,
63
+ "freeze_backbone_batch_norms": true,
64
+ "hidden_expansion": 1.0,
65
+ "id2label": {
66
+ "0": "baseball-bat",
67
+ "1": "basketball",
68
+ "2": "car",
69
+ "3": "football",
70
+ "4": "human",
71
+ "5": "luggage",
72
+ "6": "mattress",
73
+ "7": "motorcycle",
74
+ "8": "skis",
75
+ "9": "snowboard",
76
+ "10": "soccer-ball",
77
+ "11": "stop-sign",
78
+ "12": "tennis-racket",
79
+ "13": "umbrella",
80
+ "14": "volleyball"
81
+ },
82
+ "initializer_bias_prior_prob": null,
83
+ "initializer_range": 0.01,
84
+ "is_encoder_decoder": true,
85
+ "label2id": {
86
+ "baseball-bat": 0,
87
+ "basketball": 1,
88
+ "car": 2,
89
+ "football": 3,
90
+ "human": 4,
91
+ "luggage": 5,
92
+ "mattress": 6,
93
+ "motorcycle": 7,
94
+ "skis": 8,
95
+ "snowboard": 9,
96
+ "soccer-ball": 10,
97
+ "stop-sign": 11,
98
+ "tennis-racket": 12,
99
+ "umbrella": 13,
100
+ "volleyball": 14
101
+ },
102
+ "label_noise_ratio": 0.5,
103
+ "layer_norm_eps": 1e-05,
104
+ "learn_initial_query": false,
105
+ "matcher_alpha": 0.25,
106
+ "matcher_bbox_cost": 5.0,
107
+ "matcher_class_cost": 2.0,
108
+ "matcher_gamma": 2.0,
109
+ "matcher_giou_cost": 2.0,
110
+ "model_type": "rt_detr",
111
+ "normalize_before": false,
112
+ "num_denoising": 100,
113
+ "num_feature_levels": 3,
114
+ "num_queries": 300,
115
+ "positional_encoding_temperature": 10000,
116
+ "torch_dtype": "float32",
117
+ "transformers_version": "4.47.0",
118
+ "use_focal_loss": true,
119
+ "use_pretrained_backbone": false,
120
+ "use_timm_backbone": false,
121
+ "weight_loss_bbox": 5.0,
122
+ "weight_loss_giou": 2.0,
123
+ "weight_loss_vfl": 1.0,
124
+ "with_box_refine": true
125
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:12f0ce0c51716b570542d253e28fcb337a3eb0575c8a2345ce0796a6575549a3
3
+ size 171641556
preprocessor_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_convert_annotations": true,
3
+ "do_normalize": false,
4
+ "do_pad": true,
5
+ "do_rescale": true,
6
+ "do_resize": true,
7
+ "format": "coco_detection",
8
+ "image_mean": [
9
+ 0.485,
10
+ 0.456,
11
+ 0.406
12
+ ],
13
+ "image_processor_type": "RTDetrImageProcessor",
14
+ "image_std": [
15
+ 0.229,
16
+ 0.224,
17
+ 0.225
18
+ ],
19
+ "pad_size": {
20
+ "height": 640,
21
+ "width": 640
22
+ },
23
+ "resample": 2,
24
+ "rescale_factor": 0.00392156862745098,
25
+ "size": {
26
+ "max_height": 640,
27
+ "max_width": 640
28
+ }
29
+ }
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f1d204b7c3d8c7980fa7cbeb2cf1673c3feb34a01e4193028aec2e0053aa3d3d
3
+ size 5432