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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: 1.3461
- Map: 0.2811
- Map 50: 0.561
- Map 75: 0.239
- Map Small: 0.0945
- Map Medium: 0.2317
- Map Large: 0.419
- Mar 1: 0.2736
- Mar 10: 0.4208
- Mar 100: 0.4388
- Mar Small: 0.2191
- Mar Medium: 0.3871
- Mar Large: 0.598
- Map Coverall: 0.5394
- Mar 100 Coverall: 0.6554
- Map Face Shield: 0.2284
- Mar 100 Face Shield: 0.4405
- Map Gloves: 0.1791
- Mar 100 Gloves: 0.3598
- Map Goggles: 0.1786
- Mar 100 Goggles: 0.3354
- Map Mask: 0.2802
- Mar 100 Mask: 0.4027
## 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 | 107 | 2.4496 | 0.0083 | 0.0289 | 0.0024 | 0.0047 | 0.01 | 0.0114 | 0.019 | 0.0813 | 0.1191 | 0.0915 | 0.1324 | 0.1166 | 0.0124 | 0.136 | 0.0099 | 0.1278 | 0.0067 | 0.1192 | 0.0 | 0.0 | 0.0124 | 0.2124 |
| No log | 2.0 | 214 | 2.2684 | 0.0299 | 0.0782 | 0.0173 | 0.0074 | 0.0189 | 0.0401 | 0.0639 | 0.1661 | 0.1995 | 0.0976 | 0.1604 | 0.2428 | 0.0954 | 0.391 | 0.0145 | 0.1772 | 0.0077 | 0.1871 | 0.0 | 0.0 | 0.0322 | 0.2422 |
| No log | 3.0 | 321 | 2.0298 | 0.0535 | 0.1159 | 0.0446 | 0.0097 | 0.0477 | 0.0618 | 0.0981 | 0.2257 | 0.268 | 0.133 | 0.2193 | 0.3214 | 0.1778 | 0.5667 | 0.0256 | 0.2215 | 0.0099 | 0.2138 | 0.0008 | 0.0323 | 0.0533 | 0.3058 |
| No log | 4.0 | 428 | 1.8945 | 0.0859 | 0.1853 | 0.0702 | 0.0334 | 0.0778 | 0.0961 | 0.1189 | 0.293 | 0.3341 | 0.1919 | 0.2761 | 0.4265 | 0.2585 | 0.6189 | 0.049 | 0.3177 | 0.0166 | 0.2567 | 0.0041 | 0.1538 | 0.1011 | 0.3231 |
| 3.4087 | 5.0 | 535 | 1.8465 | 0.0983 | 0.2227 | 0.0737 | 0.031 | 0.0773 | 0.1063 | 0.1557 | 0.308 | 0.3463 | 0.1614 | 0.2826 | 0.486 | 0.3287 | 0.6045 | 0.0574 | 0.3468 | 0.036 | 0.2786 | 0.0086 | 0.2369 | 0.061 | 0.2644 |
| 3.4087 | 6.0 | 642 | 1.7933 | 0.1135 | 0.2609 | 0.0872 | 0.029 | 0.0843 | 0.1564 | 0.1418 | 0.3147 | 0.3511 | 0.1587 | 0.2775 | 0.5219 | 0.382 | 0.6018 | 0.0429 | 0.3215 | 0.0267 | 0.2728 | 0.011 | 0.2169 | 0.1048 | 0.3427 |
| 3.4087 | 7.0 | 749 | 1.7358 | 0.128 | 0.2893 | 0.1046 | 0.0681 | 0.1009 | 0.1695 | 0.1657 | 0.3336 | 0.371 | 0.202 | 0.3124 | 0.5316 | 0.3881 | 0.5892 | 0.0586 | 0.3747 | 0.0395 | 0.3089 | 0.0332 | 0.2569 | 0.1203 | 0.3253 |
| 3.4087 | 8.0 | 856 | 1.6967 | 0.1554 | 0.346 | 0.1184 | 0.0488 | 0.1298 | 0.2155 | 0.1863 | 0.3443 | 0.372 | 0.1588 | 0.3188 | 0.5313 | 0.4219 | 0.5959 | 0.0906 | 0.3658 | 0.0653 | 0.3058 | 0.0395 | 0.2569 | 0.1595 | 0.3356 |
| 3.4087 | 9.0 | 963 | 1.6399 | 0.1636 | 0.3504 | 0.1231 | 0.0682 | 0.139 | 0.2298 | 0.1889 | 0.3603 | 0.3918 | 0.2191 | 0.3224 | 0.5498 | 0.418 | 0.5883 | 0.0996 | 0.4038 | 0.0647 | 0.3232 | 0.0303 | 0.2708 | 0.2056 | 0.3729 |
| 1.5778 | 10.0 | 1070 | 1.5569 | 0.1838 | 0.3943 | 0.143 | 0.0643 | 0.1485 | 0.2628 | 0.2179 | 0.3785 | 0.3994 | 0.2143 | 0.3385 | 0.5573 | 0.4564 | 0.6185 | 0.1166 | 0.3899 | 0.091 | 0.3165 | 0.0554 | 0.3108 | 0.1994 | 0.3613 |
| 1.5778 | 11.0 | 1177 | 1.5197 | 0.1939 | 0.4116 | 0.1664 | 0.081 | 0.1464 | 0.2871 | 0.2228 | 0.3794 | 0.4032 | 0.1872 | 0.3522 | 0.5597 | 0.4738 | 0.6203 | 0.1204 | 0.4089 | 0.0977 | 0.3058 | 0.0806 | 0.3231 | 0.197 | 0.3582 |
| 1.5778 | 12.0 | 1284 | 1.4805 | 0.2164 | 0.466 | 0.1818 | 0.0903 | 0.1561 | 0.3301 | 0.2355 | 0.3812 | 0.4044 | 0.1933 | 0.3425 | 0.5688 | 0.4865 | 0.6279 | 0.1528 | 0.4418 | 0.122 | 0.321 | 0.0801 | 0.28 | 0.2405 | 0.3511 |
| 1.5778 | 13.0 | 1391 | 1.4775 | 0.216 | 0.4679 | 0.1811 | 0.096 | 0.1596 | 0.3276 | 0.2327 | 0.3889 | 0.4121 | 0.2207 | 0.3467 | 0.5831 | 0.4643 | 0.6054 | 0.1596 | 0.438 | 0.1273 | 0.3299 | 0.0984 | 0.3231 | 0.2303 | 0.364 |
| 1.5778 | 14.0 | 1498 | 1.4550 | 0.2185 | 0.4864 | 0.16 | 0.0813 | 0.1483 | 0.3481 | 0.2396 | 0.3863 | 0.409 | 0.2272 | 0.3341 | 0.5899 | 0.4974 | 0.6428 | 0.1488 | 0.4203 | 0.143 | 0.325 | 0.0954 | 0.2985 | 0.2082 | 0.3587 |
| 1.3087 | 15.0 | 1605 | 1.4381 | 0.2388 | 0.4949 | 0.2116 | 0.0844 | 0.184 | 0.3583 | 0.2521 | 0.3961 | 0.4194 | 0.1964 | 0.3474 | 0.5867 | 0.5148 | 0.6432 | 0.1774 | 0.4228 | 0.1375 | 0.3152 | 0.1241 | 0.3385 | 0.2401 | 0.3773 |
| 1.3087 | 16.0 | 1712 | 1.4094 | 0.2482 | 0.5241 | 0.2015 | 0.0931 | 0.1922 | 0.3754 | 0.2535 | 0.4039 | 0.4216 | 0.2291 | 0.3709 | 0.576 | 0.5054 | 0.6419 | 0.1876 | 0.4114 | 0.1622 | 0.3393 | 0.1283 | 0.3338 | 0.2578 | 0.3818 |
| 1.3087 | 17.0 | 1819 | 1.4044 | 0.2528 | 0.5311 | 0.2088 | 0.096 | 0.2052 | 0.3609 | 0.2595 | 0.4056 | 0.4228 | 0.223 | 0.3795 | 0.5587 | 0.516 | 0.6396 | 0.2009 | 0.4177 | 0.1449 | 0.3384 | 0.143 | 0.3354 | 0.2593 | 0.3831 |
| 1.3087 | 18.0 | 1926 | 1.3968 | 0.2581 | 0.5282 | 0.2107 | 0.101 | 0.2083 | 0.3787 | 0.2659 | 0.4174 | 0.4363 | 0.2289 | 0.3908 | 0.5821 | 0.5132 | 0.6387 | 0.213 | 0.4797 | 0.1584 | 0.3371 | 0.1375 | 0.3431 | 0.2682 | 0.3827 |
| 1.1363 | 19.0 | 2033 | 1.3735 | 0.2592 | 0.5349 | 0.2235 | 0.0869 | 0.2076 | 0.3936 | 0.2661 | 0.4127 | 0.4335 | 0.2159 | 0.3829 | 0.5907 | 0.5222 | 0.6414 | 0.2115 | 0.4468 | 0.1608 | 0.3549 | 0.1408 | 0.3431 | 0.2609 | 0.3813 |
| 1.1363 | 20.0 | 2140 | 1.3686 | 0.266 | 0.5447 | 0.2204 | 0.0897 | 0.2138 | 0.3875 | 0.268 | 0.4117 | 0.4326 | 0.2102 | 0.3875 | 0.5781 | 0.5323 | 0.6446 | 0.1933 | 0.4418 | 0.1727 | 0.3558 | 0.1537 | 0.3246 | 0.278 | 0.396 |
| 1.1363 | 21.0 | 2247 | 1.3672 | 0.2659 | 0.5446 | 0.2266 | 0.0859 | 0.2198 | 0.3884 | 0.2687 | 0.4164 | 0.4339 | 0.2135 | 0.3914 | 0.5779 | 0.5341 | 0.6505 | 0.1966 | 0.419 | 0.1624 | 0.3513 | 0.1698 | 0.3554 | 0.2668 | 0.3933 |
| 1.1363 | 22.0 | 2354 | 1.3658 | 0.2731 | 0.5472 | 0.2303 | 0.095 | 0.2174 | 0.4119 | 0.27 | 0.4179 | 0.4383 | 0.202 | 0.3904 | 0.5994 | 0.5311 | 0.6473 | 0.2131 | 0.4494 | 0.179 | 0.3545 | 0.1672 | 0.3492 | 0.2754 | 0.3911 |
| 1.1363 | 23.0 | 2461 | 1.3644 | 0.2692 | 0.5458 | 0.228 | 0.0937 | 0.2188 | 0.4008 | 0.2681 | 0.4205 | 0.4394 | 0.2104 | 0.3876 | 0.6031 | 0.534 | 0.6518 | 0.2028 | 0.4418 | 0.175 | 0.3594 | 0.1635 | 0.3477 | 0.2708 | 0.3964 |
| 1.0307 | 24.0 | 2568 | 1.3586 | 0.269 | 0.5419 | 0.2327 | 0.0933 | 0.2161 | 0.4067 | 0.2699 | 0.4208 | 0.439 | 0.2168 | 0.392 | 0.5983 | 0.5384 | 0.6527 | 0.2045 | 0.443 | 0.1728 | 0.3536 | 0.1581 | 0.3508 | 0.2709 | 0.3951 |
| 1.0307 | 25.0 | 2675 | 1.3503 | 0.2788 | 0.5573 | 0.239 | 0.0992 | 0.2301 | 0.4157 | 0.273 | 0.4225 | 0.4416 | 0.2261 | 0.388 | 0.6083 | 0.5361 | 0.6581 | 0.2253 | 0.4519 | 0.1805 | 0.3634 | 0.1742 | 0.3338 | 0.2779 | 0.4009 |
| 1.0307 | 26.0 | 2782 | 1.3441 | 0.2803 | 0.5605 | 0.2394 | 0.0922 | 0.2291 | 0.4206 | 0.2702 | 0.4213 | 0.4406 | 0.2174 | 0.387 | 0.6034 | 0.5392 | 0.6604 | 0.2319 | 0.4481 | 0.1831 | 0.3634 | 0.1761 | 0.3369 | 0.2711 | 0.3942 |
| 1.0307 | 27.0 | 2889 | 1.3461 | 0.2811 | 0.5603 | 0.2465 | 0.0939 | 0.23 | 0.4185 | 0.2741 | 0.4231 | 0.4418 | 0.2217 | 0.3879 | 0.6041 | 0.537 | 0.6545 | 0.2329 | 0.4506 | 0.181 | 0.3638 | 0.1792 | 0.3385 | 0.2753 | 0.4013 |
| 1.0307 | 28.0 | 2996 | 1.3462 | 0.2799 | 0.5611 | 0.2378 | 0.0943 | 0.231 | 0.4151 | 0.2732 | 0.4211 | 0.4392 | 0.2194 | 0.3863 | 0.5988 | 0.5376 | 0.655 | 0.2291 | 0.4456 | 0.179 | 0.3616 | 0.176 | 0.3323 | 0.2775 | 0.4013 |
| 0.9602 | 29.0 | 3103 | 1.3458 | 0.2811 | 0.5599 | 0.2393 | 0.094 | 0.2311 | 0.4197 | 0.2734 | 0.4208 | 0.4385 | 0.2191 | 0.3862 | 0.5986 | 0.5393 | 0.6559 | 0.2282 | 0.4405 | 0.1785 | 0.3594 | 0.1788 | 0.3338 | 0.2806 | 0.4031 |
| 0.9602 | 30.0 | 3210 | 1.3461 | 0.2811 | 0.561 | 0.239 | 0.0945 | 0.2317 | 0.419 | 0.2736 | 0.4208 | 0.4388 | 0.2191 | 0.3871 | 0.598 | 0.5394 | 0.6554 | 0.2284 | 0.4405 | 0.1791 | 0.3598 | 0.1786 | 0.3354 | 0.2802 | 0.4027 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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