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---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-101
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 [facebook/detr-resnet-101](https://huggingface.co/facebook/detr-resnet-101) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3489
- Map: 0.2197
- Map 50: 0.4408
- Map 75: 0.1896
- Map Small: 0.0734
- Map Medium: 0.1903
- Map Large: 0.3159
- Mar 1: 0.2516
- Mar 10: 0.4459
- Mar 100: 0.4733
- Mar Small: 0.191
- Mar Medium: 0.4214
- Mar Large: 0.6208
- Map Coverall: 0.4922
- Mar 100 Coverall: 0.6752
- Map Face Shield: 0.1239
- Mar 100 Face Shield: 0.4392
- Map Gloves: 0.1397
- Mar 100 Gloves: 0.4259
- Map Goggles: 0.0782
- Mar 100 Goggles: 0.42
- Map Mask: 0.2645
- Mar 100 Mask: 0.4062
## 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 | 2.2906 | 0.0222 | 0.0441 | 0.02 | 0.0042 | 0.0229 | 0.0243 | 0.0624 | 0.1415 | 0.1926 | 0.052 | 0.1457 | 0.2191 | 0.0902 | 0.5595 | 0.0 | 0.0 | 0.0106 | 0.1839 | 0.0 | 0.0 | 0.0103 | 0.2196 |
| No log | 2.0 | 214 | 2.2644 | 0.0368 | 0.0827 | 0.0263 | 0.0071 | 0.0254 | 0.0396 | 0.059 | 0.1417 | 0.1885 | 0.0671 | 0.1532 | 0.197 | 0.1528 | 0.5108 | 0.0 | 0.0 | 0.0102 | 0.2013 | 0.0 | 0.0 | 0.0209 | 0.2302 |
| No log | 3.0 | 321 | 2.1753 | 0.0446 | 0.108 | 0.0328 | 0.0103 | 0.0392 | 0.0454 | 0.0729 | 0.1561 | 0.1818 | 0.0786 | 0.1465 | 0.19 | 0.1766 | 0.505 | 0.0 | 0.0 | 0.0152 | 0.1817 | 0.0 | 0.0 | 0.0313 | 0.2222 |
| No log | 4.0 | 428 | 2.0441 | 0.0708 | 0.1548 | 0.0557 | 0.0094 | 0.0532 | 0.0746 | 0.0863 | 0.1814 | 0.1966 | 0.0738 | 0.1496 | 0.2101 | 0.2703 | 0.5491 | 0.0 | 0.0 | 0.032 | 0.2138 | 0.0 | 0.0 | 0.0515 | 0.22 |
| 2.0459 | 5.0 | 535 | 1.8798 | 0.0896 | 0.1805 | 0.0813 | 0.012 | 0.0648 | 0.0977 | 0.0895 | 0.2014 | 0.2246 | 0.081 | 0.1749 | 0.2519 | 0.3432 | 0.6018 | 0.0088 | 0.019 | 0.0326 | 0.2402 | 0.0 | 0.0 | 0.0635 | 0.2622 |
| 2.0459 | 6.0 | 642 | 1.8768 | 0.0888 | 0.1898 | 0.0727 | 0.0176 | 0.0618 | 0.1025 | 0.0974 | 0.2118 | 0.2366 | 0.0936 | 0.1639 | 0.2877 | 0.3342 | 0.6113 | 0.0102 | 0.081 | 0.0409 | 0.2536 | 0.0001 | 0.0046 | 0.0585 | 0.2324 |
| 2.0459 | 7.0 | 749 | 1.8465 | 0.0917 | 0.2075 | 0.0735 | 0.0216 | 0.0758 | 0.1166 | 0.0993 | 0.2008 | 0.2114 | 0.0748 | 0.1657 | 0.2472 | 0.3279 | 0.5905 | 0.0187 | 0.0443 | 0.0297 | 0.1862 | 0.0 | 0.0 | 0.0824 | 0.236 |
| 2.0459 | 8.0 | 856 | 1.7855 | 0.1165 | 0.2639 | 0.0908 | 0.0309 | 0.1054 | 0.1401 | 0.1341 | 0.2522 | 0.2767 | 0.0914 | 0.2412 | 0.3087 | 0.3517 | 0.6122 | 0.035 | 0.1684 | 0.0605 | 0.2902 | 0.0076 | 0.0215 | 0.1279 | 0.2911 |
| 2.0459 | 9.0 | 963 | 1.7916 | 0.1089 | 0.2494 | 0.0794 | 0.0287 | 0.087 | 0.1542 | 0.1341 | 0.282 | 0.3076 | 0.1564 | 0.2707 | 0.3343 | 0.3475 | 0.5685 | 0.0525 | 0.2797 | 0.0412 | 0.3063 | 0.0044 | 0.0754 | 0.099 | 0.308 |
| 1.6481 | 10.0 | 1070 | 1.6954 | 0.13 | 0.288 | 0.0955 | 0.0547 | 0.1057 | 0.1728 | 0.1643 | 0.3253 | 0.3494 | 0.1481 | 0.3027 | 0.4404 | 0.4015 | 0.6144 | 0.0393 | 0.2823 | 0.0652 | 0.3362 | 0.018 | 0.2185 | 0.1261 | 0.2956 |
| 1.6481 | 11.0 | 1177 | 1.7003 | 0.1424 | 0.3156 | 0.1053 | 0.0356 | 0.1306 | 0.1797 | 0.1699 | 0.3168 | 0.3385 | 0.1057 | 0.2948 | 0.4284 | 0.3823 | 0.6203 | 0.0518 | 0.2684 | 0.0809 | 0.308 | 0.0254 | 0.1569 | 0.1718 | 0.3391 |
| 1.6481 | 12.0 | 1284 | 1.6607 | 0.1468 | 0.3287 | 0.1131 | 0.0482 | 0.1304 | 0.1974 | 0.185 | 0.3226 | 0.3403 | 0.1284 | 0.2845 | 0.43 | 0.3794 | 0.5991 | 0.0699 | 0.2734 | 0.0715 | 0.3112 | 0.0238 | 0.1908 | 0.1892 | 0.3271 |
| 1.6481 | 13.0 | 1391 | 1.5862 | 0.1479 | 0.3321 | 0.1154 | 0.0532 | 0.1332 | 0.1939 | 0.1686 | 0.3415 | 0.3611 | 0.1666 | 0.3319 | 0.4261 | 0.4009 | 0.6275 | 0.0778 | 0.2835 | 0.0665 | 0.3263 | 0.0194 | 0.2354 | 0.1751 | 0.3329 |
| 1.6481 | 14.0 | 1498 | 1.6090 | 0.156 | 0.3327 | 0.1277 | 0.0447 | 0.1329 | 0.2319 | 0.1894 | 0.3776 | 0.4062 | 0.1785 | 0.357 | 0.5088 | 0.4333 | 0.6437 | 0.0546 | 0.3848 | 0.0923 | 0.3759 | 0.0302 | 0.2677 | 0.1694 | 0.3591 |
| 1.4268 | 15.0 | 1605 | 1.4913 | 0.1795 | 0.3855 | 0.147 | 0.0629 | 0.1506 | 0.2349 | 0.2076 | 0.3961 | 0.4235 | 0.2045 | 0.3634 | 0.5405 | 0.4682 | 0.6523 | 0.0713 | 0.3532 | 0.0941 | 0.3638 | 0.0461 | 0.3662 | 0.2179 | 0.3822 |
| 1.4268 | 16.0 | 1712 | 1.5350 | 0.1775 | 0.404 | 0.1384 | 0.0649 | 0.1484 | 0.2563 | 0.2119 | 0.3822 | 0.4094 | 0.1624 | 0.3624 | 0.5271 | 0.4532 | 0.6473 | 0.0644 | 0.3392 | 0.0806 | 0.3406 | 0.074 | 0.3538 | 0.2154 | 0.3662 |
| 1.4268 | 17.0 | 1819 | 1.4915 | 0.1842 | 0.3823 | 0.1568 | 0.0591 | 0.1542 | 0.2608 | 0.2168 | 0.3984 | 0.4208 | 0.1613 | 0.3758 | 0.5317 | 0.4509 | 0.6586 | 0.0853 | 0.3595 | 0.0951 | 0.3728 | 0.0471 | 0.3231 | 0.2428 | 0.3902 |
| 1.4268 | 18.0 | 1926 | 1.4537 | 0.1943 | 0.4042 | 0.1637 | 0.0724 | 0.1683 | 0.2693 | 0.2178 | 0.414 | 0.4384 | 0.1963 | 0.386 | 0.5681 | 0.4548 | 0.6577 | 0.0928 | 0.3772 | 0.1061 | 0.371 | 0.0684 | 0.3723 | 0.2494 | 0.4138 |
| 1.2822 | 19.0 | 2033 | 1.4585 | 0.1947 | 0.4081 | 0.1622 | 0.056 | 0.1612 | 0.2822 | 0.2239 | 0.4019 | 0.4303 | 0.1415 | 0.3811 | 0.5779 | 0.4742 | 0.6568 | 0.0916 | 0.3911 | 0.0974 | 0.3719 | 0.0701 | 0.3523 | 0.2404 | 0.3796 |
| 1.2822 | 20.0 | 2140 | 1.4307 | 0.2048 | 0.4048 | 0.1845 | 0.0582 | 0.179 | 0.2957 | 0.2286 | 0.4145 | 0.437 | 0.1719 | 0.3827 | 0.5799 | 0.4801 | 0.6541 | 0.102 | 0.381 | 0.1017 | 0.3701 | 0.091 | 0.3723 | 0.2491 | 0.4076 |
| 1.2822 | 21.0 | 2247 | 1.3939 | 0.1981 | 0.421 | 0.1641 | 0.0716 | 0.1697 | 0.2914 | 0.2249 | 0.4264 | 0.45 | 0.2087 | 0.3874 | 0.5846 | 0.4618 | 0.6685 | 0.1003 | 0.3886 | 0.1179 | 0.4228 | 0.0725 | 0.38 | 0.2378 | 0.3902 |
| 1.2822 | 22.0 | 2354 | 1.3966 | 0.2084 | 0.4238 | 0.1814 | 0.0638 | 0.1836 | 0.2981 | 0.2372 | 0.4322 | 0.455 | 0.1738 | 0.4012 | 0.6097 | 0.4764 | 0.6626 | 0.0987 | 0.4051 | 0.135 | 0.4098 | 0.0797 | 0.4015 | 0.252 | 0.396 |
| 1.2822 | 23.0 | 2461 | 1.3867 | 0.2125 | 0.4346 | 0.182 | 0.0781 | 0.1874 | 0.3082 | 0.2534 | 0.432 | 0.4603 | 0.1989 | 0.3963 | 0.6137 | 0.4686 | 0.6626 | 0.115 | 0.4241 | 0.1394 | 0.4147 | 0.0814 | 0.3938 | 0.2581 | 0.4062 |
| 1.1474 | 24.0 | 2568 | 1.3617 | 0.2177 | 0.4413 | 0.1898 | 0.0759 | 0.1939 | 0.3081 | 0.2521 | 0.4427 | 0.4719 | 0.2093 | 0.4277 | 0.6013 | 0.4865 | 0.6761 | 0.1186 | 0.4278 | 0.1469 | 0.4259 | 0.0852 | 0.4308 | 0.2512 | 0.3987 |
| 1.1474 | 25.0 | 2675 | 1.3695 | 0.215 | 0.4353 | 0.1889 | 0.0712 | 0.1881 | 0.3099 | 0.2553 | 0.4463 | 0.4727 | 0.1949 | 0.4258 | 0.6194 | 0.4879 | 0.6748 | 0.1128 | 0.4215 | 0.1426 | 0.4286 | 0.0771 | 0.44 | 0.2545 | 0.3987 |
| 1.1474 | 26.0 | 2782 | 1.3575 | 0.2177 | 0.433 | 0.1898 | 0.073 | 0.1879 | 0.316 | 0.2586 | 0.4454 | 0.4703 | 0.1913 | 0.4133 | 0.6285 | 0.493 | 0.682 | 0.1262 | 0.4228 | 0.1371 | 0.4241 | 0.0757 | 0.4231 | 0.2564 | 0.3996 |
| 1.1474 | 27.0 | 2889 | 1.3664 | 0.2161 | 0.4328 | 0.1848 | 0.0711 | 0.1846 | 0.314 | 0.2507 | 0.4425 | 0.4686 | 0.1885 | 0.4181 | 0.6185 | 0.4908 | 0.6775 | 0.1186 | 0.4165 | 0.1402 | 0.4246 | 0.0759 | 0.4277 | 0.2547 | 0.3969 |
| 1.1474 | 28.0 | 2996 | 1.3482 | 0.2188 | 0.4406 | 0.1864 | 0.0731 | 0.1891 | 0.317 | 0.2517 | 0.4463 | 0.4704 | 0.1906 | 0.4181 | 0.6175 | 0.491 | 0.6752 | 0.1219 | 0.4266 | 0.1388 | 0.4196 | 0.0776 | 0.4231 | 0.2647 | 0.4076 |
| 1.0794 | 29.0 | 3103 | 1.3481 | 0.2189 | 0.4402 | 0.1884 | 0.0732 | 0.1885 | 0.3173 | 0.2519 | 0.4459 | 0.4728 | 0.1923 | 0.4175 | 0.6232 | 0.491 | 0.673 | 0.1237 | 0.4354 | 0.1392 | 0.425 | 0.0768 | 0.4215 | 0.264 | 0.4089 |
| 1.0794 | 30.0 | 3210 | 1.3489 | 0.2197 | 0.4408 | 0.1896 | 0.0734 | 0.1903 | 0.3159 | 0.2516 | 0.4459 | 0.4733 | 0.191 | 0.4214 | 0.6208 | 0.4922 | 0.6752 | 0.1239 | 0.4392 | 0.1397 | 0.4259 | 0.0782 | 0.42 | 0.2645 | 0.4062 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
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