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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: test
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. -->
# test
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: 1.1603
- Map: 0.2667
- Map 50: 0.5044
- Map 75: 0.2456
- Map Small: 0.0909
- Map Medium: 0.2038
- Map Large: 0.3504
- Mar 1: 0.2709
- Mar 10: 0.4322
- Mar 100: 0.4537
- Mar Small: 0.1705
- Mar Medium: 0.3988
- Mar Large: 0.5803
- Map Coverall: 0.5892
- Mar 100 Coverall: 0.7071
- Map Face Shield: 0.1292
- Mar 100 Face Shield: 0.4657
- Map Gloves: 0.1967
- Mar 100 Gloves: 0.3534
- Map Goggles: 0.1026
- Mar 100 Goggles: 0.2918
- Map Mask: 0.316
- Mar 100 Mask: 0.4506
## 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 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 | 91 | 1.8372 | 0.007 | 0.0258 | 0.0011 | 0.0141 | 0.0074 | 0.0074 | 0.0155 | 0.0699 | 0.1041 | 0.0717 | 0.1388 | 0.1297 | 0.0 | 0.0161 | 0.0011 | 0.0039 | 0.004 | 0.1531 | 0.0005 | 0.0682 | 0.0291 | 0.2794 |
| No log | 2.0 | 182 | 1.6868 | 0.0122 | 0.0409 | 0.0051 | 0.0178 | 0.0127 | 0.0159 | 0.0234 | 0.1069 | 0.1472 | 0.1082 | 0.1665 | 0.1779 | 0.003 | 0.1219 | 0.0001 | 0.001 | 0.0101 | 0.2014 | 0.0016 | 0.0518 | 0.0464 | 0.3601 |
| No log | 3.0 | 273 | 1.5610 | 0.027 | 0.0704 | 0.0145 | 0.0209 | 0.0215 | 0.0511 | 0.0768 | 0.1903 | 0.2325 | 0.1097 | 0.2337 | 0.2895 | 0.0339 | 0.3714 | 0.0019 | 0.0471 | 0.0181 | 0.2523 | 0.0026 | 0.0965 | 0.0784 | 0.3951 |
| No log | 4.0 | 364 | 1.5762 | 0.0407 | 0.0899 | 0.0339 | 0.011 | 0.0217 | 0.0606 | 0.0826 | 0.1865 | 0.2398 | 0.104 | 0.2439 | 0.2762 | 0.1194 | 0.5415 | 0.0011 | 0.0441 | 0.0049 | 0.183 | 0.0008 | 0.0576 | 0.0772 | 0.3728 |
| No log | 5.0 | 455 | 1.4866 | 0.0584 | 0.1347 | 0.0434 | 0.0265 | 0.0517 | 0.0705 | 0.1131 | 0.2302 | 0.2768 | 0.1274 | 0.2489 | 0.3144 | 0.1524 | 0.546 | 0.0068 | 0.0755 | 0.0229 | 0.274 | 0.017 | 0.0965 | 0.0932 | 0.3922 |
| 2.2578 | 6.0 | 546 | 1.4517 | 0.0782 | 0.1742 | 0.0608 | 0.0352 | 0.0653 | 0.0921 | 0.1191 | 0.2638 | 0.3064 | 0.1173 | 0.2795 | 0.3505 | 0.2028 | 0.6438 | 0.0052 | 0.1196 | 0.0309 | 0.2671 | 0.0075 | 0.1118 | 0.1448 | 0.3897 |
| 2.2578 | 7.0 | 637 | 1.4567 | 0.1202 | 0.2463 | 0.1019 | 0.0548 | 0.1205 | 0.1364 | 0.163 | 0.3228 | 0.356 | 0.1594 | 0.3255 | 0.4543 | 0.3099 | 0.7063 | 0.0102 | 0.2412 | 0.0491 | 0.2744 | 0.0557 | 0.1753 | 0.176 | 0.3831 |
| 2.2578 | 8.0 | 728 | 1.4039 | 0.1446 | 0.2979 | 0.1181 | 0.0584 | 0.1175 | 0.1695 | 0.1537 | 0.3259 | 0.3556 | 0.128 | 0.3103 | 0.4379 | 0.4289 | 0.6817 | 0.0142 | 0.2598 | 0.0604 | 0.2816 | 0.0327 | 0.1612 | 0.1867 | 0.3938 |
| 2.2578 | 9.0 | 819 | 1.3552 | 0.1623 | 0.3277 | 0.1455 | 0.0586 | 0.1179 | 0.2124 | 0.1759 | 0.3576 | 0.3833 | 0.1318 | 0.3387 | 0.4908 | 0.4853 | 0.6973 | 0.0153 | 0.2853 | 0.0861 | 0.3155 | 0.0257 | 0.2071 | 0.1988 | 0.4111 |
| 2.2578 | 10.0 | 910 | 1.3194 | 0.1819 | 0.3602 | 0.165 | 0.0737 | 0.126 | 0.2357 | 0.1881 | 0.3606 | 0.3881 | 0.1939 | 0.3337 | 0.4953 | 0.4961 | 0.6723 | 0.0203 | 0.3284 | 0.0938 | 0.3072 | 0.0449 | 0.2094 | 0.2543 | 0.423 |
| 1.2495 | 11.0 | 1001 | 1.3209 | 0.1814 | 0.3609 | 0.1521 | 0.067 | 0.1267 | 0.2353 | 0.188 | 0.3616 | 0.3892 | 0.2079 | 0.3159 | 0.5058 | 0.495 | 0.6643 | 0.025 | 0.3284 | 0.1066 | 0.3029 | 0.0508 | 0.2494 | 0.2297 | 0.4008 |
| 1.2495 | 12.0 | 1092 | 1.2817 | 0.1922 | 0.3946 | 0.154 | 0.0681 | 0.1501 | 0.2335 | 0.2042 | 0.3822 | 0.4057 | 0.1483 | 0.3511 | 0.5242 | 0.5286 | 0.6808 | 0.0544 | 0.3961 | 0.1025 | 0.3076 | 0.0462 | 0.2365 | 0.2295 | 0.4074 |
| 1.2495 | 13.0 | 1183 | 1.2797 | 0.207 | 0.4039 | 0.1838 | 0.0767 | 0.1446 | 0.2743 | 0.2117 | 0.3881 | 0.4101 | 0.1362 | 0.356 | 0.5387 | 0.5433 | 0.6893 | 0.0566 | 0.3745 | 0.1286 | 0.3061 | 0.0427 | 0.2671 | 0.2636 | 0.4136 |
| 1.2495 | 14.0 | 1274 | 1.2330 | 0.2165 | 0.416 | 0.1999 | 0.081 | 0.1565 | 0.2767 | 0.2247 | 0.3935 | 0.4251 | 0.1558 | 0.3763 | 0.5399 | 0.5671 | 0.6946 | 0.0579 | 0.3725 | 0.1453 | 0.331 | 0.0371 | 0.3071 | 0.2751 | 0.4202 |
| 1.2495 | 15.0 | 1365 | 1.2150 | 0.2214 | 0.4317 | 0.1966 | 0.0766 | 0.1686 | 0.287 | 0.2243 | 0.3993 | 0.4316 | 0.1896 | 0.3783 | 0.5457 | 0.5626 | 0.6866 | 0.075 | 0.4186 | 0.1465 | 0.339 | 0.0527 | 0.2812 | 0.2701 | 0.4325 |
| 1.2495 | 16.0 | 1456 | 1.1971 | 0.2229 | 0.4395 | 0.1913 | 0.0832 | 0.1531 | 0.2993 | 0.2335 | 0.4103 | 0.4389 | 0.1593 | 0.3698 | 0.5667 | 0.5625 | 0.6888 | 0.0567 | 0.4461 | 0.1539 | 0.3466 | 0.0716 | 0.2882 | 0.2698 | 0.4247 |
| 1.0777 | 17.0 | 1547 | 1.1886 | 0.2435 | 0.4578 | 0.228 | 0.0881 | 0.174 | 0.312 | 0.2487 | 0.4166 | 0.4476 | 0.1758 | 0.3803 | 0.581 | 0.5767 | 0.6978 | 0.1008 | 0.449 | 0.1588 | 0.3538 | 0.0615 | 0.2824 | 0.3194 | 0.4551 |
| 1.0777 | 18.0 | 1638 | 1.1980 | 0.2414 | 0.4659 | 0.2154 | 0.0895 | 0.1714 | 0.3089 | 0.2464 | 0.4181 | 0.4423 | 0.1624 | 0.3736 | 0.5643 | 0.5718 | 0.6875 | 0.1057 | 0.449 | 0.1619 | 0.343 | 0.0644 | 0.2894 | 0.3033 | 0.4424 |
| 1.0777 | 19.0 | 1729 | 1.1748 | 0.2448 | 0.4786 | 0.2174 | 0.0917 | 0.1801 | 0.3185 | 0.2488 | 0.424 | 0.4502 | 0.1551 | 0.3875 | 0.5786 | 0.5706 | 0.6902 | 0.1289 | 0.4745 | 0.1626 | 0.3473 | 0.0568 | 0.2918 | 0.3051 | 0.4473 |
| 1.0777 | 20.0 | 1820 | 1.1770 | 0.2544 | 0.4702 | 0.2366 | 0.0924 | 0.189 | 0.3271 | 0.2632 | 0.4292 | 0.4507 | 0.148 | 0.3992 | 0.5778 | 0.5753 | 0.7085 | 0.1107 | 0.4696 | 0.1718 | 0.339 | 0.0916 | 0.2906 | 0.3225 | 0.4457 |
| 1.0777 | 21.0 | 1911 | 1.1731 | 0.2539 | 0.4917 | 0.2379 | 0.0914 | 0.1924 | 0.3282 | 0.2559 | 0.4247 | 0.4493 | 0.1665 | 0.3907 | 0.5753 | 0.5741 | 0.6991 | 0.113 | 0.4471 | 0.1814 | 0.3444 | 0.0832 | 0.2976 | 0.3177 | 0.4584 |
| 0.9577 | 22.0 | 2002 | 1.1567 | 0.2622 | 0.4932 | 0.2434 | 0.0956 | 0.2006 | 0.3363 | 0.2639 | 0.4339 | 0.4564 | 0.1785 | 0.4013 | 0.5797 | 0.5848 | 0.7018 | 0.1226 | 0.4539 | 0.1924 | 0.357 | 0.0861 | 0.3082 | 0.325 | 0.4609 |
| 0.9577 | 23.0 | 2093 | 1.1649 | 0.2666 | 0.4975 | 0.2456 | 0.091 | 0.2019 | 0.35 | 0.2678 | 0.433 | 0.4573 | 0.1587 | 0.4036 | 0.5832 | 0.5831 | 0.7009 | 0.1563 | 0.4882 | 0.1947 | 0.3477 | 0.0803 | 0.3035 | 0.3186 | 0.4461 |
| 0.9577 | 24.0 | 2184 | 1.1525 | 0.2658 | 0.4949 | 0.2438 | 0.095 | 0.1972 | 0.3465 | 0.2677 | 0.4357 | 0.4585 | 0.1666 | 0.3978 | 0.5878 | 0.5886 | 0.704 | 0.1243 | 0.4588 | 0.1972 | 0.3617 | 0.0938 | 0.3082 | 0.3253 | 0.4597 |
| 0.9577 | 25.0 | 2275 | 1.1496 | 0.2665 | 0.4958 | 0.251 | 0.0927 | 0.1984 | 0.3513 | 0.2733 | 0.4334 | 0.4561 | 0.1568 | 0.3959 | 0.5837 | 0.5879 | 0.7071 | 0.1312 | 0.4696 | 0.1969 | 0.3599 | 0.0947 | 0.2918 | 0.3215 | 0.4519 |
| 0.9577 | 26.0 | 2366 | 1.1596 | 0.2667 | 0.5005 | 0.2434 | 0.092 | 0.1975 | 0.3517 | 0.2691 | 0.4346 | 0.4566 | 0.1714 | 0.3994 | 0.582 | 0.5894 | 0.7089 | 0.1298 | 0.4686 | 0.1964 | 0.357 | 0.0981 | 0.2988 | 0.3197 | 0.4494 |
| 0.9577 | 27.0 | 2457 | 1.1595 | 0.2679 | 0.5033 | 0.2455 | 0.0918 | 0.2041 | 0.3531 | 0.2706 | 0.4341 | 0.4549 | 0.1695 | 0.4039 | 0.5765 | 0.5868 | 0.7067 | 0.1368 | 0.4745 | 0.1972 | 0.3545 | 0.1001 | 0.2894 | 0.3186 | 0.4494 |
| 0.8804 | 28.0 | 2548 | 1.1584 | 0.2673 | 0.5038 | 0.2465 | 0.0916 | 0.2018 | 0.3518 | 0.2703 | 0.4332 | 0.4542 | 0.1698 | 0.3978 | 0.5809 | 0.5888 | 0.7067 | 0.1321 | 0.4676 | 0.1964 | 0.3542 | 0.1032 | 0.2929 | 0.3163 | 0.4498 |
| 0.8804 | 29.0 | 2639 | 1.1602 | 0.2666 | 0.5041 | 0.2454 | 0.0909 | 0.2018 | 0.349 | 0.2707 | 0.4317 | 0.4538 | 0.1701 | 0.397 | 0.58 | 0.5885 | 0.7071 | 0.129 | 0.4647 | 0.1968 | 0.3531 | 0.1016 | 0.2929 | 0.3171 | 0.451 |
| 0.8804 | 30.0 | 2730 | 1.1603 | 0.2667 | 0.5044 | 0.2456 | 0.0909 | 0.2038 | 0.3504 | 0.2709 | 0.4322 | 0.4537 | 0.1705 | 0.3988 | 0.5803 | 0.5892 | 0.7071 | 0.1292 | 0.4657 | 0.1967 | 0.3534 | 0.1026 | 0.2918 | 0.316 | 0.4506 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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