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library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: conditional-detr-resnet-50_finetuned_cppe5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# conditional-detr-resnet-50_finetuned_cppe5
This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0625
- Map: 0.2889
- Map 50: 0.5213
- Map 75: 0.2755
- Map Small: 0.1022
- Map Medium: 0.229
- Map Large: 0.4272
- Mar 1: 0.3222
- Mar 10: 0.4831
- Mar 100: 0.5016
- Mar Small: 0.2614
- Mar Medium: 0.4179
- Mar Large: 0.6587
- Map Coverall: 0.5718
- Mar 100 Coverall: 0.6954
- Map Face Shield: 0.2333
- Mar 100 Face Shield: 0.4986
- Map Gloves: 0.2051
- Mar 100 Gloves: 0.4271
- Map Goggles: 0.1597
- Mar 100 Goggles: 0.4629
- Map Mask: 0.2745
- Mar 100 Mask: 0.4239
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 30
### Training results
| 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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| 1.9147 | 1.0 | 106 | 1.8194 | 0.018 | 0.0388 | 0.0143 | 0.0021 | 0.0124 | 0.0239 | 0.0327 | 0.0914 | 0.1369 | 0.0511 | 0.1158 | 0.1784 | 0.066 | 0.2723 | 0.0016 | 0.0141 | 0.002 | 0.1633 | 0.0 | 0.0242 | 0.0204 | 0.2105 |
| 1.7779 | 2.0 | 212 | 1.6795 | 0.0258 | 0.0566 | 0.0213 | 0.0028 | 0.0269 | 0.045 | 0.0581 | 0.1398 | 0.2003 | 0.0736 | 0.1451 | 0.276 | 0.0948 | 0.4672 | 0.0018 | 0.0183 | 0.0034 | 0.2156 | 0.0 | 0.0161 | 0.0288 | 0.2842 |
| 1.5384 | 3.0 | 318 | 1.5198 | 0.0564 | 0.1102 | 0.0497 | 0.011 | 0.0461 | 0.0728 | 0.1032 | 0.2112 | 0.2611 | 0.0954 | 0.19 | 0.3563 | 0.1985 | 0.5672 | 0.0195 | 0.0803 | 0.006 | 0.2704 | 0.0026 | 0.0452 | 0.0554 | 0.3426 |
| 1.4396 | 4.0 | 424 | 1.4693 | 0.068 | 0.1268 | 0.0605 | 0.0083 | 0.0559 | 0.0844 | 0.1045 | 0.2328 | 0.2914 | 0.0959 | 0.2147 | 0.3865 | 0.2221 | 0.6308 | 0.0243 | 0.1169 | 0.0062 | 0.2503 | 0.0022 | 0.0887 | 0.0854 | 0.3703 |
| 1.346 | 5.0 | 530 | 1.3865 | 0.1092 | 0.211 | 0.0886 | 0.0299 | 0.0947 | 0.1306 | 0.147 | 0.3056 | 0.3498 | 0.1688 | 0.2721 | 0.4676 | 0.3744 | 0.6385 | 0.0243 | 0.2676 | 0.0141 | 0.299 | 0.017 | 0.1774 | 0.1161 | 0.3665 |
| 1.4945 | 6.0 | 636 | 1.3785 | 0.1192 | 0.2391 | 0.1004 | 0.0284 | 0.1022 | 0.14 | 0.1468 | 0.3166 | 0.3547 | 0.1625 | 0.2961 | 0.468 | 0.4067 | 0.6149 | 0.0358 | 0.269 | 0.0376 | 0.3347 | 0.0148 | 0.2032 | 0.1011 | 0.3517 |
| 1.3374 | 7.0 | 742 | 1.3494 | 0.1227 | 0.2446 | 0.1104 | 0.0224 | 0.0971 | 0.1504 | 0.1771 | 0.3492 | 0.3849 | 0.1914 | 0.3082 | 0.5158 | 0.4317 | 0.619 | 0.0343 | 0.3535 | 0.0329 | 0.3397 | 0.009 | 0.2403 | 0.1056 | 0.3718 |
| 1.2146 | 8.0 | 848 | 1.2911 | 0.1438 | 0.2789 | 0.1279 | 0.07 | 0.1074 | 0.2004 | 0.1887 | 0.3793 | 0.4099 | 0.2098 | 0.3261 | 0.5631 | 0.4433 | 0.6128 | 0.0426 | 0.369 | 0.073 | 0.3935 | 0.0302 | 0.2903 | 0.1298 | 0.3837 |
| 1.2948 | 9.0 | 954 | 1.2916 | 0.142 | 0.2761 | 0.1166 | 0.0521 | 0.1147 | 0.1801 | 0.1982 | 0.3779 | 0.4107 | 0.1976 | 0.3197 | 0.5616 | 0.4229 | 0.6103 | 0.0509 | 0.3718 | 0.0672 | 0.3935 | 0.0368 | 0.2871 | 0.1321 | 0.3909 |
| 1.2078 | 10.0 | 1060 | 1.2753 | 0.1507 | 0.3144 | 0.1235 | 0.0328 | 0.1191 | 0.2269 | 0.2093 | 0.3851 | 0.4132 | 0.1723 | 0.332 | 0.5746 | 0.4389 | 0.6256 | 0.0735 | 0.369 | 0.0662 | 0.3714 | 0.0271 | 0.3177 | 0.1477 | 0.3823 |
| 1.2587 | 11.0 | 1166 | 1.2508 | 0.1734 | 0.3524 | 0.1442 | 0.0515 | 0.1426 | 0.2446 | 0.2113 | 0.3937 | 0.4257 | 0.1954 | 0.3409 | 0.5844 | 0.463 | 0.6436 | 0.0627 | 0.3859 | 0.1096 | 0.3799 | 0.0553 | 0.3387 | 0.1762 | 0.3804 |
| 1.1698 | 12.0 | 1272 | 1.1786 | 0.2005 | 0.3877 | 0.1683 | 0.1016 | 0.1568 | 0.2834 | 0.238 | 0.424 | 0.4521 | 0.2352 | 0.3716 | 0.5995 | 0.506 | 0.6631 | 0.1129 | 0.4676 | 0.1215 | 0.4095 | 0.0575 | 0.3081 | 0.2048 | 0.412 |
| 1.2067 | 13.0 | 1378 | 1.2097 | 0.1984 | 0.387 | 0.1682 | 0.0614 | 0.1482 | 0.2911 | 0.229 | 0.4181 | 0.4454 | 0.217 | 0.3519 | 0.6179 | 0.5025 | 0.6697 | 0.103 | 0.4366 | 0.1196 | 0.3899 | 0.0618 | 0.3565 | 0.205 | 0.3742 |
| 1.0912 | 14.0 | 1484 | 1.1591 | 0.2216 | 0.419 | 0.2006 | 0.0819 | 0.1857 | 0.3055 | 0.2625 | 0.4402 | 0.4714 | 0.2437 | 0.3902 | 0.615 | 0.5025 | 0.6759 | 0.1505 | 0.469 | 0.13 | 0.4055 | 0.083 | 0.3887 | 0.2422 | 0.4177 |
| 1.0154 | 15.0 | 1590 | 1.1474 | 0.2306 | 0.4327 | 0.2099 | 0.1035 | 0.1847 | 0.333 | 0.2706 | 0.4434 | 0.4683 | 0.2241 | 0.3922 | 0.6141 | 0.5212 | 0.6672 | 0.159 | 0.4718 | 0.1442 | 0.3935 | 0.0876 | 0.3935 | 0.2411 | 0.4153 |
| 1.0772 | 16.0 | 1696 | 1.1345 | 0.2388 | 0.4498 | 0.2175 | 0.1053 | 0.1906 | 0.3505 | 0.2811 | 0.4483 | 0.4791 | 0.2289 | 0.3974 | 0.6313 | 0.5251 | 0.6692 | 0.1643 | 0.4845 | 0.1485 | 0.4131 | 0.1073 | 0.4194 | 0.2489 | 0.4096 |
| 0.9185 | 17.0 | 1802 | 1.1253 | 0.2409 | 0.4471 | 0.2173 | 0.1159 | 0.1991 | 0.3476 | 0.279 | 0.4538 | 0.4783 | 0.253 | 0.4055 | 0.6226 | 0.5242 | 0.6559 | 0.1469 | 0.4606 | 0.1676 | 0.4211 | 0.1137 | 0.429 | 0.2523 | 0.4249 |
| 1.0736 | 18.0 | 1908 | 1.1187 | 0.2507 | 0.4656 | 0.2378 | 0.1003 | 0.2144 | 0.3554 | 0.2878 | 0.4592 | 0.4858 | 0.2265 | 0.426 | 0.6152 | 0.5353 | 0.6785 | 0.1635 | 0.4606 | 0.1699 | 0.4387 | 0.1412 | 0.4339 | 0.2437 | 0.4172 |
| 1.0021 | 19.0 | 2014 | 1.0987 | 0.2608 | 0.4736 | 0.2522 | 0.1262 | 0.2172 | 0.3734 | 0.2981 | 0.4526 | 0.4809 | 0.237 | 0.4049 | 0.6321 | 0.5396 | 0.6713 | 0.1529 | 0.4803 | 0.1888 | 0.4201 | 0.1616 | 0.421 | 0.2611 | 0.412 |
| 1.0613 | 20.0 | 2120 | 1.1144 | 0.2563 | 0.4785 | 0.2276 | 0.0917 | 0.2102 | 0.3691 | 0.2895 | 0.4472 | 0.4732 | 0.2493 | 0.3923 | 0.6189 | 0.5421 | 0.6621 | 0.1623 | 0.4521 | 0.1872 | 0.4317 | 0.1383 | 0.4145 | 0.2515 | 0.4057 |
| 1.0576 | 21.0 | 2226 | 1.0888 | 0.2827 | 0.5059 | 0.271 | 0.1041 | 0.2359 | 0.4061 | 0.3106 | 0.4658 | 0.4922 | 0.2639 | 0.4076 | 0.6432 | 0.5516 | 0.6831 | 0.2145 | 0.5056 | 0.1897 | 0.4276 | 0.1896 | 0.4274 | 0.2678 | 0.4172 |
| 0.8949 | 22.0 | 2332 | 1.0893 | 0.2762 | 0.5078 | 0.2489 | 0.1207 | 0.2241 | 0.4014 | 0.3038 | 0.4662 | 0.489 | 0.2413 | 0.4026 | 0.6519 | 0.5583 | 0.6856 | 0.1908 | 0.4789 | 0.2028 | 0.4226 | 0.1652 | 0.4403 | 0.2635 | 0.4177 |
| 1.0853 | 23.0 | 2438 | 1.0747 | 0.275 | 0.501 | 0.2602 | 0.1144 | 0.2267 | 0.3966 | 0.3049 | 0.4722 | 0.4958 | 0.2632 | 0.412 | 0.646 | 0.5569 | 0.6908 | 0.1743 | 0.493 | 0.202 | 0.4281 | 0.1771 | 0.4581 | 0.2649 | 0.4091 |
| 1.0098 | 24.0 | 2544 | 1.0623 | 0.28 | 0.5081 | 0.263 | 0.1136 | 0.2199 | 0.4101 | 0.311 | 0.479 | 0.5011 | 0.2629 | 0.4175 | 0.653 | 0.5705 | 0.6949 | 0.2057 | 0.5014 | 0.2023 | 0.4256 | 0.1551 | 0.4613 | 0.2665 | 0.4225 |
| 0.8466 | 25.0 | 2650 | 1.0682 | 0.2862 | 0.514 | 0.2748 | 0.105 | 0.2306 | 0.4217 | 0.3173 | 0.4813 | 0.5009 | 0.2669 | 0.4195 | 0.6565 | 0.5691 | 0.6944 | 0.221 | 0.4972 | 0.2088 | 0.4241 | 0.1613 | 0.4645 | 0.271 | 0.4244 |
| 0.9067 | 26.0 | 2756 | 1.0638 | 0.2881 | 0.5225 | 0.276 | 0.1085 | 0.2309 | 0.4219 | 0.3183 | 0.4802 | 0.4991 | 0.2475 | 0.4205 | 0.6539 | 0.5723 | 0.6938 | 0.232 | 0.4944 | 0.2051 | 0.4246 | 0.158 | 0.4597 | 0.2734 | 0.423 |
| 0.8462 | 27.0 | 2862 | 1.0629 | 0.288 | 0.5182 | 0.2679 | 0.1013 | 0.2252 | 0.4272 | 0.3191 | 0.4807 | 0.5004 | 0.261 | 0.4176 | 0.6546 | 0.57 | 0.6933 | 0.2337 | 0.4986 | 0.2057 | 0.4286 | 0.158 | 0.4565 | 0.2728 | 0.4249 |
| 0.8771 | 28.0 | 2968 | 1.0642 | 0.2901 | 0.524 | 0.2781 | 0.1028 | 0.2299 | 0.4267 | 0.3215 | 0.4821 | 0.5009 | 0.2603 | 0.4192 | 0.6555 | 0.5725 | 0.6949 | 0.2346 | 0.4972 | 0.2055 | 0.4251 | 0.1634 | 0.4629 | 0.2744 | 0.4244 |
| 0.8022 | 29.0 | 3074 | 1.0626 | 0.2885 | 0.5212 | 0.2758 | 0.1017 | 0.229 | 0.427 | 0.322 | 0.4829 | 0.5013 | 0.2589 | 0.4183 | 0.6588 | 0.5718 | 0.6959 | 0.2309 | 0.4972 | 0.206 | 0.4276 | 0.1595 | 0.4613 | 0.2744 | 0.4244 |
| 0.8245 | 30.0 | 3180 | 1.0625 | 0.2889 | 0.5213 | 0.2755 | 0.1022 | 0.229 | 0.4272 | 0.3222 | 0.4831 | 0.5016 | 0.2614 | 0.4179 | 0.6587 | 0.5718 | 0.6954 | 0.2333 | 0.4986 | 0.2051 | 0.4271 | 0.1597 | 0.4629 | 0.2745 | 0.4239 |
### Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
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