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---
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr_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. -->
# detr_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: 1.2426
- Map: 0.268
- Map 50: 0.5294
- Map 75: 0.2419
- Map Small: 0.1163
- Map Medium: 0.2288
- Map Large: 0.5006
- Mar 1: 0.2865
- Mar 10: 0.4475
- Mar 100: 0.4749
- Mar Small: 0.3002
- Mar Medium: 0.4623
- Mar Large: 0.7345
- Map Coverall: 0.5546
- Mar 100 Coverall: 0.6736
- Map Face Shield: 0.1674
- Mar 100 Face Shield: 0.4833
- Map Gloves: 0.1944
- Mar 100 Gloves: 0.3662
- Map Goggles: 0.1199
- Mar 100 Goggles: 0.4421
- Map Mask: 0.3036
- Mar 100 Mask: 0.4092
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| No log | 1.0 | 102 | 2.3847 | 0.008 | 0.0259 | 0.0031 | 0.0071 | 0.0113 | 0.0323 | 0.0303 | 0.1094 | 0.1661 | 0.1002 | 0.1711 | 0.2087 | 0.0105 | 0.207 | 0.0034 | 0.0681 | 0.0078 | 0.2167 | 0.0025 | 0.0807 | 0.0156 | 0.2583 |
| No log | 2.0 | 204 | 2.1346 | 0.0292 | 0.0819 | 0.0147 | 0.0126 | 0.0268 | 0.042 | 0.0773 | 0.1631 | 0.2064 | 0.0815 | 0.1912 | 0.2543 | 0.0873 | 0.3791 | 0.0083 | 0.1153 | 0.0116 | 0.2069 | 0.0 | 0.0 | 0.0388 | 0.3306 |
| No log | 3.0 | 306 | 2.0183 | 0.0546 | 0.1289 | 0.0413 | 0.0288 | 0.0352 | 0.0606 | 0.1234 | 0.2329 | 0.2765 | 0.1078 | 0.2436 | 0.3393 | 0.1671 | 0.5567 | 0.0187 | 0.2167 | 0.0094 | 0.2157 | 0.0346 | 0.0912 | 0.0431 | 0.3024 |
| No log | 4.0 | 408 | 1.9305 | 0.0779 | 0.1742 | 0.0587 | 0.02 | 0.0476 | 0.1114 | 0.1417 | 0.2692 | 0.3059 | 0.0926 | 0.2783 | 0.4861 | 0.27 | 0.59 | 0.0335 | 0.3208 | 0.0214 | 0.2377 | 0.0036 | 0.086 | 0.061 | 0.2951 |
| 3.3072 | 5.0 | 510 | 1.7155 | 0.1186 | 0.2742 | 0.0935 | 0.0303 | 0.0871 | 0.2195 | 0.1434 | 0.3145 | 0.3401 | 0.1573 | 0.3076 | 0.5985 | 0.3762 | 0.5582 | 0.0213 | 0.2569 | 0.0463 | 0.2892 | 0.0081 | 0.2333 | 0.1414 | 0.3626 |
| 3.3072 | 6.0 | 612 | 1.6430 | 0.1371 | 0.301 | 0.1037 | 0.0347 | 0.1046 | 0.2527 | 0.1733 | 0.3374 | 0.3664 | 0.1605 | 0.3393 | 0.5973 | 0.4248 | 0.601 | 0.0216 | 0.2875 | 0.0572 | 0.3059 | 0.0243 | 0.2877 | 0.1577 | 0.35 |
| 3.3072 | 7.0 | 714 | 1.5879 | 0.1537 | 0.345 | 0.1218 | 0.0534 | 0.1358 | 0.2768 | 0.1933 | 0.3528 | 0.3807 | 0.1858 | 0.3554 | 0.6497 | 0.4326 | 0.6124 | 0.034 | 0.3486 | 0.0719 | 0.2917 | 0.0246 | 0.2877 | 0.2056 | 0.3631 |
| 3.3072 | 8.0 | 816 | 1.5310 | 0.1649 | 0.3587 | 0.1398 | 0.0579 | 0.1333 | 0.3036 | 0.1925 | 0.3729 | 0.3946 | 0.1854 | 0.3742 | 0.6476 | 0.4674 | 0.6353 | 0.0415 | 0.3722 | 0.0933 | 0.301 | 0.0387 | 0.3333 | 0.1836 | 0.3311 |
| 3.3072 | 9.0 | 918 | 1.4758 | 0.1789 | 0.3922 | 0.1478 | 0.0668 | 0.1372 | 0.3167 | 0.2241 | 0.3745 | 0.405 | 0.2063 | 0.3752 | 0.6691 | 0.4539 | 0.6199 | 0.063 | 0.4139 | 0.1041 | 0.3108 | 0.0375 | 0.3053 | 0.236 | 0.3752 |
| 1.4864 | 10.0 | 1020 | 1.4622 | 0.1735 | 0.3827 | 0.1333 | 0.05 | 0.1411 | 0.354 | 0.2103 | 0.371 | 0.3951 | 0.183 | 0.3664 | 0.6752 | 0.4784 | 0.6313 | 0.053 | 0.3903 | 0.1182 | 0.3186 | 0.0195 | 0.3053 | 0.1985 | 0.3301 |
| 1.4864 | 11.0 | 1122 | 1.4252 | 0.1858 | 0.4134 | 0.1496 | 0.0591 | 0.1632 | 0.3561 | 0.2227 | 0.3873 | 0.4144 | 0.1911 | 0.4137 | 0.6645 | 0.4794 | 0.6488 | 0.0752 | 0.4153 | 0.1131 | 0.3034 | 0.0292 | 0.3439 | 0.2319 | 0.3607 |
| 1.4864 | 12.0 | 1224 | 1.3893 | 0.1973 | 0.4218 | 0.1643 | 0.0749 | 0.169 | 0.4139 | 0.242 | 0.4054 | 0.4302 | 0.2226 | 0.4175 | 0.6991 | 0.4854 | 0.6413 | 0.0662 | 0.4292 | 0.1319 | 0.3397 | 0.0503 | 0.3561 | 0.2529 | 0.3845 |
| 1.4864 | 13.0 | 1326 | 1.3891 | 0.1998 | 0.431 | 0.1596 | 0.0675 | 0.1829 | 0.3762 | 0.2277 | 0.3962 | 0.4222 | 0.1979 | 0.4311 | 0.7011 | 0.504 | 0.6428 | 0.0911 | 0.4333 | 0.1384 | 0.3353 | 0.0552 | 0.3702 | 0.2101 | 0.3296 |
| 1.4864 | 14.0 | 1428 | 1.3981 | 0.193 | 0.42 | 0.1614 | 0.0698 | 0.1693 | 0.3523 | 0.235 | 0.3978 | 0.4271 | 0.2379 | 0.42 | 0.6729 | 0.4962 | 0.6557 | 0.0681 | 0.4278 | 0.136 | 0.3451 | 0.0493 | 0.3298 | 0.2155 | 0.3772 |
| 1.2306 | 15.0 | 1530 | 1.3472 | 0.217 | 0.4617 | 0.1785 | 0.0857 | 0.1817 | 0.4264 | 0.2416 | 0.4046 | 0.4329 | 0.2377 | 0.4143 | 0.7007 | 0.5137 | 0.6363 | 0.0968 | 0.4611 | 0.1571 | 0.3475 | 0.0484 | 0.3509 | 0.2689 | 0.3684 |
| 1.2306 | 16.0 | 1632 | 1.3450 | 0.227 | 0.4747 | 0.1915 | 0.0861 | 0.1891 | 0.4373 | 0.2521 | 0.4104 | 0.439 | 0.2503 | 0.4112 | 0.7344 | 0.5183 | 0.6428 | 0.1179 | 0.4514 | 0.1589 | 0.3289 | 0.0684 | 0.3912 | 0.2717 | 0.3806 |
| 1.2306 | 17.0 | 1734 | 1.2998 | 0.2359 | 0.4833 | 0.202 | 0.1089 | 0.1972 | 0.4426 | 0.2661 | 0.4303 | 0.4475 | 0.2792 | 0.4221 | 0.6999 | 0.5251 | 0.6463 | 0.12 | 0.4556 | 0.1646 | 0.3466 | 0.0857 | 0.393 | 0.284 | 0.3961 |
| 1.2306 | 18.0 | 1836 | 1.2995 | 0.2376 | 0.4866 | 0.1989 | 0.0926 | 0.2056 | 0.4487 | 0.2711 | 0.4325 | 0.4575 | 0.2798 | 0.4319 | 0.7195 | 0.522 | 0.6542 | 0.1299 | 0.475 | 0.1636 | 0.3544 | 0.0838 | 0.4018 | 0.2884 | 0.4019 |
| 1.2306 | 19.0 | 1938 | 1.2998 | 0.2362 | 0.4948 | 0.1954 | 0.1036 | 0.1905 | 0.4647 | 0.2563 | 0.4277 | 0.4446 | 0.249 | 0.4216 | 0.7165 | 0.5308 | 0.6672 | 0.1334 | 0.4722 | 0.1829 | 0.3407 | 0.0721 | 0.3772 | 0.2617 | 0.3655 |
| 1.0733 | 20.0 | 2040 | 1.2773 | 0.2513 | 0.5082 | 0.2298 | 0.1057 | 0.2148 | 0.4873 | 0.2723 | 0.4393 | 0.4678 | 0.2749 | 0.4514 | 0.7437 | 0.5342 | 0.6652 | 0.1499 | 0.4556 | 0.1754 | 0.3534 | 0.1101 | 0.4561 | 0.287 | 0.4087 |
| 1.0733 | 21.0 | 2142 | 1.2668 | 0.2516 | 0.5077 | 0.2323 | 0.1048 | 0.2104 | 0.4929 | 0.2758 | 0.4353 | 0.4592 | 0.2787 | 0.4287 | 0.7393 | 0.541 | 0.6692 | 0.1386 | 0.4653 | 0.1778 | 0.3525 | 0.1074 | 0.4018 | 0.2933 | 0.4073 |
| 1.0733 | 22.0 | 2244 | 1.2665 | 0.2496 | 0.5166 | 0.2143 | 0.114 | 0.2045 | 0.4759 | 0.2609 | 0.4314 | 0.454 | 0.2708 | 0.4246 | 0.7292 | 0.5355 | 0.6577 | 0.1393 | 0.4556 | 0.182 | 0.3657 | 0.1069 | 0.4 | 0.2842 | 0.3913 |
| 1.0733 | 23.0 | 2346 | 1.2512 | 0.2585 | 0.5258 | 0.2298 | 0.1196 | 0.2121 | 0.4884 | 0.2789 | 0.4465 | 0.4695 | 0.2991 | 0.4453 | 0.7262 | 0.5455 | 0.6672 | 0.1491 | 0.4833 | 0.1899 | 0.373 | 0.1149 | 0.4211 | 0.2931 | 0.4029 |
| 1.0733 | 24.0 | 2448 | 1.2511 | 0.2639 | 0.5275 | 0.2388 | 0.1198 | 0.2218 | 0.511 | 0.2845 | 0.4464 | 0.47 | 0.2911 | 0.4511 | 0.7377 | 0.5482 | 0.6657 | 0.1549 | 0.4694 | 0.192 | 0.3725 | 0.125 | 0.4386 | 0.2994 | 0.4039 |
| 0.9823 | 25.0 | 2550 | 1.2495 | 0.2629 | 0.5392 | 0.2309 | 0.1173 | 0.2213 | 0.4926 | 0.2828 | 0.4429 | 0.467 | 0.2888 | 0.4478 | 0.7363 | 0.549 | 0.6672 | 0.1633 | 0.4792 | 0.1931 | 0.3652 | 0.1181 | 0.4263 | 0.2908 | 0.3971 |
| 0.9823 | 26.0 | 2652 | 1.2470 | 0.2653 | 0.5276 | 0.2364 | 0.1136 | 0.2258 | 0.5082 | 0.2884 | 0.4486 | 0.4715 | 0.3017 | 0.4567 | 0.7313 | 0.5535 | 0.6701 | 0.1641 | 0.475 | 0.192 | 0.3672 | 0.1162 | 0.4368 | 0.3007 | 0.4083 |
| 0.9823 | 27.0 | 2754 | 1.2471 | 0.2661 | 0.5287 | 0.2366 | 0.1138 | 0.227 | 0.5013 | 0.2809 | 0.4483 | 0.4736 | 0.2986 | 0.4636 | 0.7286 | 0.5519 | 0.6711 | 0.1687 | 0.4806 | 0.1934 | 0.3676 | 0.1135 | 0.4404 | 0.3031 | 0.4083 |
| 0.9823 | 28.0 | 2856 | 1.2434 | 0.2673 | 0.5291 | 0.242 | 0.1156 | 0.229 | 0.5028 | 0.2866 | 0.4462 | 0.4745 | 0.3008 | 0.461 | 0.7367 | 0.5555 | 0.6736 | 0.1651 | 0.4806 | 0.1951 | 0.3662 | 0.1179 | 0.4421 | 0.3028 | 0.4102 |
| 0.9823 | 29.0 | 2958 | 1.2427 | 0.2676 | 0.5272 | 0.2425 | 0.116 | 0.2286 | 0.5 | 0.2863 | 0.4472 | 0.4745 | 0.299 | 0.4623 | 0.7343 | 0.554 | 0.6721 | 0.1675 | 0.4833 | 0.1942 | 0.3667 | 0.1195 | 0.4404 | 0.3027 | 0.4102 |
| 0.9316 | 30.0 | 3060 | 1.2426 | 0.268 | 0.5294 | 0.2419 | 0.1163 | 0.2288 | 0.5006 | 0.2865 | 0.4475 | 0.4749 | 0.3002 | 0.4623 | 0.7345 | 0.5546 | 0.6736 | 0.1674 | 0.4833 | 0.1944 | 0.3662 | 0.1199 | 0.4421 | 0.3036 | 0.4092 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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