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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: 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: 1.3299
- Map: 0.0678
- Map 50: 0.1359
- Map 75: 0.0621
- Map Small: 0.0953
- Map Medium: 0.0947
- Map Large: 0.0707
- Mar 1: 0.123
- Mar 10: 0.3315
- Mar 100: 0.4317
- Mar Small: 0.4556
- Mar Medium: 0.3046
- Mar Large: 0.4536
- Map Coverall: 0.1683
- Mar 100 Coverall: 0.5644
- Map Face Shield: 0.02
- Mar 100 Face Shield: 0.2595
- Map Gloves: 0.0512
- Mar 100 Gloves: 0.4817
- Map Goggles: 0.0345
- Mar 100 Goggles: 0.3015
- Map Mask: 0.0647
- Mar 100 Mask: 0.5511
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| No log | 1.0 | 107 | 2.0850 | 0.0082 | 0.0334 | 0.0018 | 0.001 | 0.0046 | 0.009 | 0.0157 | 0.0658 | 0.1123 | 0.0333 | 0.0983 | 0.1162 | 0.0321 | 0.2923 | 0.0 | 0.0051 | 0.0021 | 0.1098 | 0.0 | 0.0 | 0.0067 | 0.1542 |
| No log | 2.0 | 214 | 1.7616 | 0.0139 | 0.0413 | 0.0061 | 0.0005 | 0.047 | 0.0148 | 0.032 | 0.097 | 0.1704 | 0.0556 | 0.1232 | 0.1787 | 0.0492 | 0.3464 | 0.0 | 0.0 | 0.0065 | 0.1768 | 0.0 | 0.0 | 0.0136 | 0.3289 |
| No log | 3.0 | 321 | 1.8263 | 0.0213 | 0.068 | 0.0086 | 0.0047 | 0.0567 | 0.0241 | 0.036 | 0.1253 | 0.2014 | 0.1111 | 0.1304 | 0.2085 | 0.0659 | 0.5212 | 0.0001 | 0.0013 | 0.0152 | 0.1759 | 0.0 | 0.0 | 0.0252 | 0.3084 |
| No log | 4.0 | 428 | 1.7623 | 0.0254 | 0.066 | 0.0157 | 0.0151 | 0.0437 | 0.0265 | 0.0439 | 0.1393 | 0.2158 | 0.1111 | 0.1517 | 0.2252 | 0.0757 | 0.4342 | 0.0 | 0.0 | 0.0107 | 0.2241 | 0.0 | 0.0 | 0.0405 | 0.4209 |
| 2.7673 | 5.0 | 535 | 1.7402 | 0.0137 | 0.041 | 0.0051 | 0.005 | 0.0735 | 0.0146 | 0.0379 | 0.1097 | 0.1786 | 0.2556 | 0.1474 | 0.1831 | 0.046 | 0.3851 | 0.0012 | 0.0291 | 0.0021 | 0.1045 | 0.0 | 0.0 | 0.0191 | 0.3742 |
| 2.7673 | 6.0 | 642 | 1.6179 | 0.0256 | 0.0682 | 0.019 | 0.0089 | 0.0539 | 0.0273 | 0.0474 | 0.1269 | 0.2129 | 0.1778 | 0.141 | 0.2251 | 0.0673 | 0.423 | 0.001 | 0.0139 | 0.0022 | 0.1129 | 0.0074 | 0.0908 | 0.0503 | 0.424 |
| 2.7673 | 7.0 | 749 | 1.6199 | 0.0292 | 0.0672 | 0.0226 | 0.0053 | 0.0555 | 0.031 | 0.0546 | 0.145 | 0.2148 | 0.1333 | 0.1666 | 0.2271 | 0.0855 | 0.3883 | 0.0109 | 0.0139 | 0.0042 | 0.1357 | 0.0084 | 0.1015 | 0.0369 | 0.4347 |
| 2.7673 | 8.0 | 856 | 1.5755 | 0.029 | 0.0672 | 0.0219 | 0.0116 | 0.0722 | 0.0308 | 0.0558 | 0.1596 | 0.2416 | 0.2222 | 0.2017 | 0.2514 | 0.0858 | 0.4532 | 0.0026 | 0.0835 | 0.0036 | 0.1219 | 0.0095 | 0.1062 | 0.0436 | 0.4431 |
| 2.7673 | 9.0 | 963 | 1.5618 | 0.0338 | 0.0765 | 0.0277 | 0.0203 | 0.0719 | 0.0345 | 0.0474 | 0.1673 | 0.2511 | 0.2667 | 0.1616 | 0.2654 | 0.1082 | 0.5171 | 0.0002 | 0.0051 | 0.0198 | 0.2263 | 0.0047 | 0.0723 | 0.0362 | 0.4347 |
| 1.5478 | 10.0 | 1070 | 1.5111 | 0.0384 | 0.087 | 0.0319 | 0.065 | 0.0612 | 0.0407 | 0.0642 | 0.1982 | 0.2903 | 0.3222 | 0.1896 | 0.3069 | 0.0963 | 0.5284 | 0.0026 | 0.0392 | 0.0341 | 0.2871 | 0.0137 | 0.16 | 0.0453 | 0.4369 |
| 1.5478 | 11.0 | 1177 | 1.5122 | 0.0403 | 0.0922 | 0.0333 | 0.1083 | 0.072 | 0.0431 | 0.0729 | 0.2024 | 0.2958 | 0.4333 | 0.213 | 0.3086 | 0.1113 | 0.545 | 0.0052 | 0.0494 | 0.0333 | 0.2897 | 0.0142 | 0.1646 | 0.0371 | 0.4302 |
| 1.5478 | 12.0 | 1284 | 1.5083 | 0.0443 | 0.0985 | 0.0355 | 0.0534 | 0.0833 | 0.0451 | 0.0801 | 0.2004 | 0.2943 | 0.2333 | 0.2097 | 0.3095 | 0.1221 | 0.5441 | 0.0008 | 0.0114 | 0.0404 | 0.3433 | 0.0108 | 0.12 | 0.0475 | 0.4529 |
| 1.5478 | 13.0 | 1391 | 1.5374 | 0.0397 | 0.0859 | 0.0314 | 0.0861 | 0.0688 | 0.0419 | 0.0689 | 0.2201 | 0.3134 | 0.2889 | 0.2209 | 0.3291 | 0.1162 | 0.5405 | 0.003 | 0.0671 | 0.0297 | 0.3187 | 0.011 | 0.1908 | 0.0389 | 0.4498 |
| 1.5478 | 14.0 | 1498 | 1.5145 | 0.0449 | 0.1019 | 0.0344 | 0.0438 | 0.0794 | 0.0454 | 0.0684 | 0.2017 | 0.2897 | 0.3222 | 0.2005 | 0.3029 | 0.1423 | 0.5784 | 0.0009 | 0.0316 | 0.0356 | 0.2991 | 0.0089 | 0.1138 | 0.0367 | 0.4253 |
| 1.4217 | 15.0 | 1605 | 1.4832 | 0.0488 | 0.1141 | 0.0366 | 0.0474 | 0.0845 | 0.052 | 0.0798 | 0.2294 | 0.3337 | 0.3778 | 0.2367 | 0.3474 | 0.1426 | 0.5577 | 0.0033 | 0.0759 | 0.0419 | 0.4018 | 0.0214 | 0.2108 | 0.0347 | 0.4222 |
| 1.4217 | 16.0 | 1712 | 1.4627 | 0.047 | 0.1086 | 0.0344 | 0.0654 | 0.0892 | 0.0471 | 0.0896 | 0.2317 | 0.3142 | 0.3111 | 0.2416 | 0.3254 | 0.1408 | 0.5464 | 0.0053 | 0.1025 | 0.0303 | 0.3022 | 0.0119 | 0.1508 | 0.0466 | 0.4689 |
| 1.4217 | 17.0 | 1819 | 1.4152 | 0.0548 | 0.1195 | 0.0462 | 0.1189 | 0.0943 | 0.0558 | 0.097 | 0.2685 | 0.3578 | 0.3556 | 0.2809 | 0.371 | 0.1493 | 0.5234 | 0.0082 | 0.119 | 0.0401 | 0.3884 | 0.0155 | 0.2123 | 0.061 | 0.5458 |
| 1.4217 | 18.0 | 1926 | 1.4076 | 0.0506 | 0.1097 | 0.0425 | 0.054 | 0.0801 | 0.051 | 0.1038 | 0.2696 | 0.3692 | 0.3333 | 0.2823 | 0.3858 | 0.1389 | 0.5671 | 0.0109 | 0.1544 | 0.0293 | 0.3746 | 0.0142 | 0.24 | 0.0597 | 0.5098 |
| 1.3356 | 19.0 | 2033 | 1.3879 | 0.0576 | 0.1206 | 0.0504 | 0.1236 | 0.0895 | 0.0598 | 0.1222 | 0.2867 | 0.3818 | 0.3556 | 0.2535 | 0.4032 | 0.1396 | 0.5689 | 0.0161 | 0.1506 | 0.0359 | 0.4071 | 0.0333 | 0.2692 | 0.0629 | 0.5129 |
| 1.3356 | 20.0 | 2140 | 1.3471 | 0.064 | 0.1333 | 0.0581 | 0.1344 | 0.0948 | 0.0664 | 0.1268 | 0.3056 | 0.3965 | 0.3889 | 0.2996 | 0.4138 | 0.1558 | 0.5532 | 0.0217 | 0.1911 | 0.0491 | 0.4554 | 0.0253 | 0.2569 | 0.068 | 0.5258 |
| 1.3356 | 21.0 | 2247 | 1.3539 | 0.0652 | 0.1366 | 0.0549 | 0.1063 | 0.0885 | 0.0679 | 0.1163 | 0.3217 | 0.4142 | 0.4333 | 0.2995 | 0.4336 | 0.1572 | 0.5802 | 0.0178 | 0.2051 | 0.0595 | 0.4826 | 0.0254 | 0.2631 | 0.0663 | 0.54 |
| 1.3356 | 22.0 | 2354 | 1.3476 | 0.0653 | 0.1307 | 0.0583 | 0.0702 | 0.0963 | 0.0675 | 0.1116 | 0.3069 | 0.4026 | 0.4556 | 0.2928 | 0.4192 | 0.1678 | 0.568 | 0.0145 | 0.2013 | 0.0565 | 0.4848 | 0.0269 | 0.2354 | 0.061 | 0.5236 |
| 1.3356 | 23.0 | 2461 | 1.3519 | 0.064 | 0.1276 | 0.0584 | 0.0643 | 0.0999 | 0.0666 | 0.1169 | 0.3317 | 0.4235 | 0.4222 | 0.3046 | 0.4442 | 0.1609 | 0.5527 | 0.0178 | 0.2544 | 0.05 | 0.4674 | 0.0292 | 0.3 | 0.062 | 0.5431 |
| 1.2549 | 24.0 | 2568 | 1.3419 | 0.065 | 0.1327 | 0.058 | 0.0643 | 0.1002 | 0.0678 | 0.118 | 0.3265 | 0.4157 | 0.4222 | 0.295 | 0.4359 | 0.161 | 0.5833 | 0.0174 | 0.238 | 0.0546 | 0.4679 | 0.0314 | 0.26 | 0.0608 | 0.5293 |
| 1.2549 | 25.0 | 2675 | 1.3354 | 0.0687 | 0.1351 | 0.0617 | 0.0811 | 0.0904 | 0.0725 | 0.1241 | 0.3242 | 0.4217 | 0.4667 | 0.2988 | 0.4422 | 0.1643 | 0.5779 | 0.0179 | 0.2468 | 0.0521 | 0.4723 | 0.044 | 0.2646 | 0.0651 | 0.5467 |
| 1.2549 | 26.0 | 2782 | 1.3312 | 0.0679 | 0.1364 | 0.0626 | 0.083 | 0.0894 | 0.0711 | 0.1246 | 0.329 | 0.4268 | 0.4556 | 0.3039 | 0.4472 | 0.1683 | 0.5676 | 0.0201 | 0.2544 | 0.0523 | 0.4857 | 0.0349 | 0.2862 | 0.0641 | 0.54 |
| 1.2549 | 27.0 | 2889 | 1.3333 | 0.0667 | 0.1347 | 0.0615 | 0.0919 | 0.0904 | 0.0695 | 0.1237 | 0.3287 | 0.4308 | 0.4667 | 0.3055 | 0.4528 | 0.1653 | 0.568 | 0.019 | 0.2481 | 0.0513 | 0.4817 | 0.0315 | 0.3031 | 0.0666 | 0.5529 |
| 1.2549 | 28.0 | 2996 | 1.3306 | 0.0666 | 0.1343 | 0.0609 | 0.098 | 0.0899 | 0.0692 | 0.1248 | 0.3286 | 0.4284 | 0.4667 | 0.3021 | 0.4502 | 0.1666 | 0.5635 | 0.0188 | 0.2468 | 0.051 | 0.4777 | 0.0315 | 0.3 | 0.0652 | 0.5538 |
| 1.2213 | 29.0 | 3103 | 1.3300 | 0.0678 | 0.1358 | 0.0618 | 0.0955 | 0.0948 | 0.0707 | 0.1238 | 0.3319 | 0.432 | 0.4556 | 0.3046 | 0.454 | 0.1683 | 0.5649 | 0.0201 | 0.2595 | 0.0511 | 0.4826 | 0.0345 | 0.3015 | 0.0648 | 0.5516 |
| 1.2213 | 30.0 | 3210 | 1.3299 | 0.0678 | 0.1359 | 0.0621 | 0.0953 | 0.0947 | 0.0707 | 0.123 | 0.3315 | 0.4317 | 0.4556 | 0.3046 | 0.4536 | 0.1683 | 0.5644 | 0.02 | 0.2595 | 0.0512 | 0.4817 | 0.0345 | 0.3015 | 0.0647 | 0.5511 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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