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library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- trackio
- trackio:https://huggingface.co/spaces/erdoganeray/trackio
- generated_from_trainer
model-index:
- name: detr_finetuned_cppe5
results: []
---
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# 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: 1.2034
- Map: 0.2192
- Map 50: 0.4298
- Map 75: 0.1923
- Map Small: 0.0677
- Map Medium: 0.1739
- Map Large: 0.3381
- Mar 1: 0.2636
- Mar 10: 0.4234
- Mar 100: 0.4497
- Mar Small: 0.1919
- Mar Medium: 0.39
- Mar Large: 0.6217
- Map Coverall: 0.4982
- Mar 100 Coverall: 0.6387
- Map Face Shield: 0.0954
- Mar 100 Face Shield: 0.4722
- Map Gloves: 0.1506
- Mar 100 Gloves: 0.3777
- Map Goggles: 0.081
- Mar 100 Goggles: 0.3646
- Map Mask: 0.2708
- Mar 100 Mask: 0.3951
## 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_FUSED 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 | 1.7116 | 0.0274 | 0.0694 | 0.0194 | 0.0074 | 0.0217 | 0.0451 | 0.0499 | 0.1412 | 0.1925 | 0.0723 | 0.1381 | 0.2663 | 0.1103 | 0.4419 | 0.0 | 0.0013 | 0.0033 | 0.1875 | 0.0041 | 0.0754 | 0.0191 | 0.2564 |
| No log | 2.0 | 214 | 1.6186 | 0.0398 | 0.0934 | 0.0306 | 0.0222 | 0.0377 | 0.0547 | 0.1063 | 0.1982 | 0.2517 | 0.1077 | 0.1918 | 0.3492 | 0.1036 | 0.5437 | 0.0072 | 0.1316 | 0.0091 | 0.2071 | 0.016 | 0.0892 | 0.0633 | 0.2867 |
| No log | 3.0 | 321 | 1.5486 | 0.0512 | 0.11 | 0.0438 | 0.028 | 0.056 | 0.0715 | 0.1395 | 0.2594 | 0.3078 | 0.1268 | 0.2369 | 0.4292 | 0.1043 | 0.5788 | 0.0277 | 0.2203 | 0.0075 | 0.2098 | 0.043 | 0.2262 | 0.0735 | 0.304 |
| No log | 4.0 | 428 | 1.5472 | 0.0533 | 0.137 | 0.0337 | 0.0291 | 0.0638 | 0.0747 | 0.1133 | 0.2629 | 0.3105 | 0.1571 | 0.2495 | 0.4174 | 0.111 | 0.5405 | 0.0503 | 0.243 | 0.0149 | 0.2545 | 0.023 | 0.1969 | 0.0672 | 0.3173 |
| 1.5074 | 5.0 | 535 | 1.5760 | 0.0619 | 0.155 | 0.0432 | 0.0109 | 0.0605 | 0.1039 | 0.1361 | 0.2843 | 0.3224 | 0.0894 | 0.2421 | 0.4874 | 0.1516 | 0.5743 | 0.0452 | 0.3025 | 0.0229 | 0.2504 | 0.0253 | 0.2138 | 0.0645 | 0.2707 |
| 1.5074 | 6.0 | 642 | 1.4846 | 0.1036 | 0.2392 | 0.0797 | 0.0173 | 0.0873 | 0.1585 | 0.1569 | 0.3032 | 0.3376 | 0.1247 | 0.2939 | 0.4495 | 0.3186 | 0.5554 | 0.0552 | 0.2962 | 0.027 | 0.2786 | 0.0121 | 0.2169 | 0.1049 | 0.3409 |
| 1.5074 | 7.0 | 749 | 1.4449 | 0.1159 | 0.2606 | 0.0914 | 0.0252 | 0.0881 | 0.1749 | 0.1706 | 0.317 | 0.3526 | 0.1509 | 0.2933 | 0.4943 | 0.3608 | 0.5964 | 0.0381 | 0.3354 | 0.0236 | 0.2496 | 0.0208 | 0.2385 | 0.1364 | 0.3431 |
| 1.5074 | 8.0 | 856 | 1.4081 | 0.1336 | 0.3052 | 0.107 | 0.0416 | 0.0942 | 0.205 | 0.1776 | 0.3424 | 0.3707 | 0.1576 | 0.3024 | 0.5316 | 0.4067 | 0.6014 | 0.0421 | 0.3886 | 0.0556 | 0.2826 | 0.0226 | 0.2554 | 0.1411 | 0.3253 |
| 1.5074 | 9.0 | 963 | 1.3705 | 0.148 | 0.3213 | 0.1258 | 0.0293 | 0.1222 | 0.2178 | 0.1901 | 0.3571 | 0.3876 | 0.15 | 0.3371 | 0.5387 | 0.4213 | 0.6167 | 0.0594 | 0.4038 | 0.0612 | 0.2987 | 0.0259 | 0.2631 | 0.1722 | 0.3556 |
| 1.3013 | 10.0 | 1070 | 1.3602 | 0.1584 | 0.3305 | 0.1346 | 0.0362 | 0.1133 | 0.2399 | 0.1931 | 0.3557 | 0.3856 | 0.1857 | 0.3283 | 0.5278 | 0.4279 | 0.5986 | 0.0611 | 0.4 | 0.074 | 0.3107 | 0.0332 | 0.2738 | 0.1957 | 0.3449 |
| 1.3013 | 11.0 | 1177 | 1.3725 | 0.1593 | 0.3379 | 0.1367 | 0.0275 | 0.1189 | 0.247 | 0.1978 | 0.3466 | 0.3802 | 0.1397 | 0.3249 | 0.5352 | 0.4371 | 0.5982 | 0.0656 | 0.3772 | 0.087 | 0.3076 | 0.0274 | 0.2677 | 0.1794 | 0.3502 |
| 1.3013 | 12.0 | 1284 | 1.3000 | 0.1717 | 0.3617 | 0.1475 | 0.0379 | 0.1348 | 0.2565 | 0.214 | 0.3735 | 0.4053 | 0.1488 | 0.3598 | 0.5573 | 0.442 | 0.6041 | 0.0662 | 0.4241 | 0.0943 | 0.3286 | 0.0344 | 0.3 | 0.2216 | 0.3698 |
| 1.3013 | 13.0 | 1391 | 1.3342 | 0.1776 | 0.3737 | 0.1515 | 0.0374 | 0.1422 | 0.2722 | 0.2179 | 0.3591 | 0.3903 | 0.1164 | 0.3231 | 0.5675 | 0.4434 | 0.6131 | 0.0634 | 0.3975 | 0.1087 | 0.3196 | 0.0449 | 0.2615 | 0.2277 | 0.3596 |
| 1.3013 | 14.0 | 1498 | 1.2838 | 0.1807 | 0.3793 | 0.1569 | 0.0459 | 0.1462 | 0.2794 | 0.2256 | 0.3762 | 0.4115 | 0.181 | 0.3605 | 0.5631 | 0.4564 | 0.6225 | 0.0725 | 0.4038 | 0.1028 | 0.3429 | 0.054 | 0.3338 | 0.2177 | 0.3547 |
| 1.1477 | 15.0 | 1605 | 1.2723 | 0.1896 | 0.3918 | 0.1608 | 0.0399 | 0.1511 | 0.2894 | 0.2338 | 0.3942 | 0.4205 | 0.1894 | 0.3634 | 0.5764 | 0.456 | 0.6135 | 0.08 | 0.4278 | 0.1099 | 0.3397 | 0.0798 | 0.3446 | 0.2223 | 0.3769 |
| 1.1477 | 16.0 | 1712 | 1.2764 | 0.1858 | 0.376 | 0.1629 | 0.0409 | 0.149 | 0.2947 | 0.2254 | 0.3894 | 0.4239 | 0.2129 | 0.3751 | 0.5601 | 0.4561 | 0.6104 | 0.0759 | 0.4405 | 0.1123 | 0.3545 | 0.0616 | 0.3569 | 0.2234 | 0.3573 |
| 1.1477 | 17.0 | 1819 | 1.2602 | 0.1971 | 0.3992 | 0.1724 | 0.056 | 0.1717 | 0.2941 | 0.2393 | 0.4011 | 0.4286 | 0.1736 | 0.3831 | 0.5859 | 0.4613 | 0.6203 | 0.0834 | 0.4595 | 0.1347 | 0.3554 | 0.0525 | 0.3308 | 0.2534 | 0.3773 |
| 1.1477 | 18.0 | 1926 | 1.2624 | 0.1952 | 0.4039 | 0.1659 | 0.0567 | 0.1611 | 0.3026 | 0.24 | 0.3957 | 0.424 | 0.165 | 0.3847 | 0.5785 | 0.4667 | 0.618 | 0.0704 | 0.4696 | 0.1359 | 0.3598 | 0.0546 | 0.3154 | 0.2484 | 0.3573 |
| 1.0398 | 19.0 | 2033 | 1.2619 | 0.1921 | 0.3923 | 0.1678 | 0.0608 | 0.1556 | 0.3026 | 0.2384 | 0.3965 | 0.4246 | 0.1644 | 0.3761 | 0.5746 | 0.4525 | 0.6135 | 0.0848 | 0.4519 | 0.1217 | 0.3518 | 0.0623 | 0.3354 | 0.2393 | 0.3702 |
| 1.0398 | 20.0 | 2140 | 1.2340 | 0.2006 | 0.3944 | 0.1743 | 0.0616 | 0.1617 | 0.3124 | 0.237 | 0.4062 | 0.4328 | 0.1581 | 0.3849 | 0.599 | 0.4722 | 0.6225 | 0.0849 | 0.481 | 0.1327 | 0.3643 | 0.0525 | 0.3169 | 0.2607 | 0.3791 |
| 1.0398 | 21.0 | 2247 | 1.2209 | 0.205 | 0.4153 | 0.1748 | 0.046 | 0.1674 | 0.3206 | 0.2484 | 0.412 | 0.4407 | 0.1765 | 0.3841 | 0.6157 | 0.4871 | 0.6477 | 0.0893 | 0.4608 | 0.139 | 0.3692 | 0.0573 | 0.3431 | 0.2524 | 0.3827 |
| 1.0398 | 22.0 | 2354 | 1.2334 | 0.2075 | 0.4077 | 0.1805 | 0.0508 | 0.1694 | 0.3203 | 0.2509 | 0.4121 | 0.4438 | 0.1916 | 0.3892 | 0.612 | 0.486 | 0.6432 | 0.095 | 0.4835 | 0.138 | 0.3661 | 0.0597 | 0.3462 | 0.2588 | 0.38 |
| 1.0398 | 23.0 | 2461 | 1.2315 | 0.2112 | 0.4138 | 0.19 | 0.0549 | 0.1696 | 0.3282 | 0.2544 | 0.4133 | 0.4432 | 0.1927 | 0.3934 | 0.6124 | 0.4846 | 0.6459 | 0.0886 | 0.4785 | 0.1476 | 0.3705 | 0.0693 | 0.3338 | 0.2658 | 0.3871 |
| 0.9646 | 24.0 | 2568 | 1.2137 | 0.2125 | 0.4179 | 0.1841 | 0.054 | 0.1706 | 0.3298 | 0.2585 | 0.4158 | 0.4453 | 0.2018 | 0.3908 | 0.6063 | 0.4918 | 0.636 | 0.0887 | 0.4747 | 0.1446 | 0.3737 | 0.0767 | 0.3646 | 0.2608 | 0.3773 |
| 0.9646 | 25.0 | 2675 | 1.1987 | 0.2179 | 0.4262 | 0.1897 | 0.0685 | 0.1749 | 0.3361 | 0.2586 | 0.423 | 0.4512 | 0.2017 | 0.3953 | 0.624 | 0.4925 | 0.6392 | 0.0945 | 0.4684 | 0.1535 | 0.3799 | 0.0802 | 0.3723 | 0.2686 | 0.3964 |
| 0.9646 | 26.0 | 2782 | 1.2014 | 0.2193 | 0.4297 | 0.1938 | 0.0579 | 0.1756 | 0.3351 | 0.2626 | 0.4229 | 0.4498 | 0.1946 | 0.3907 | 0.6245 | 0.4939 | 0.6419 | 0.0942 | 0.4696 | 0.1526 | 0.3763 | 0.0798 | 0.3615 | 0.2761 | 0.3996 |
| 0.9646 | 27.0 | 2889 | 1.2045 | 0.2168 | 0.4253 | 0.1893 | 0.0571 | 0.1732 | 0.333 | 0.2651 | 0.4243 | 0.4501 | 0.1874 | 0.3917 | 0.6238 | 0.4938 | 0.6428 | 0.0915 | 0.4709 | 0.1489 | 0.3772 | 0.0803 | 0.3646 | 0.2696 | 0.3951 |
| 0.9646 | 28.0 | 2996 | 1.2055 | 0.2187 | 0.4276 | 0.1923 | 0.0683 | 0.1726 | 0.3369 | 0.2633 | 0.4242 | 0.45 | 0.1887 | 0.391 | 0.6225 | 0.4973 | 0.6383 | 0.0925 | 0.4696 | 0.1511 | 0.3795 | 0.0812 | 0.3646 | 0.2713 | 0.3978 |
| 0.9147 | 29.0 | 3103 | 1.2039 | 0.2191 | 0.4296 | 0.1923 | 0.0677 | 0.1742 | 0.3382 | 0.2638 | 0.4232 | 0.4499 | 0.1884 | 0.3904 | 0.6226 | 0.4974 | 0.6392 | 0.0952 | 0.4709 | 0.1506 | 0.3781 | 0.0812 | 0.3646 | 0.2713 | 0.3964 |
| 0.9147 | 30.0 | 3210 | 1.2034 | 0.2192 | 0.4298 | 0.1923 | 0.0677 | 0.1739 | 0.3381 | 0.2636 | 0.4234 | 0.4497 | 0.1919 | 0.39 | 0.6217 | 0.4982 | 0.6387 | 0.0954 | 0.4722 | 0.1506 | 0.3777 | 0.081 | 0.3646 | 0.2708 | 0.3951 |
### Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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