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---
base_model: PekingU/rtdetr_r50vd_coco_o365
tags:
- generated_from_trainer
model-index:
- name: rtdetr-r50-cppe5-finetune
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. -->
# rtdetr-r50-cppe5-finetune
This model is a fine-tuned version of [PekingU/rtdetr_r50vd_coco_o365](https://huggingface.co/PekingU/rtdetr_r50vd_coco_o365) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 9.9243
- Map: 0.4532
- Map 50: 0.66
- Map 75: 0.5228
- Map Small: 0.431
- Map Medium: 0.3515
- Map Large: 0.5415
- Mar 1: 0.3644
- Mar 10: 0.6286
- Mar 100: 0.6927
- Mar Small: 0.5962
- Mar Medium: 0.5879
- Mar Large: 0.81
- Map Coverall: 0.4755
- Mar 100 Coverall: 0.7974
- Map Face Shield: 0.4919
- Mar 100 Face Shield: 0.7176
- Map Gloves: 0.3847
- Mar 100 Gloves: 0.6593
- Map Goggles: 0.3127
- Mar 100 Goggles: 0.5793
- Map Mask: 0.6013
- Mar 100 Mask: 0.7098
## 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: linear
- num_epochs: 10
### 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 | 138.4975 | 0.0441 | 0.0808 | 0.0353 | 0.0 | 0.0247 | 0.056 | 0.0547 | 0.1243 | 0.1461 | 0.0 | 0.082 | 0.2388 | 0.2204 | 0.5937 | 0.0001 | 0.0759 | 0.0 | 0.0201 | 0.0 | 0.02 | 0.0 | 0.0209 |
| No log | 2.0 | 214 | 23.3748 | 0.0916 | 0.1786 | 0.0747 | 0.0461 | 0.0467 | 0.0912 | 0.1138 | 0.269 | 0.3528 | 0.2138 | 0.2623 | 0.4998 | 0.3271 | 0.6284 | 0.0041 | 0.3076 | 0.0078 | 0.2701 | 0.0034 | 0.2246 | 0.1156 | 0.3333 |
| No log | 3.0 | 321 | 13.3702 | 0.2057 | 0.3793 | 0.196 | 0.1007 | 0.1548 | 0.3415 | 0.2296 | 0.4115 | 0.4959 | 0.2755 | 0.4268 | 0.7117 | 0.4253 | 0.6986 | 0.0393 | 0.5051 | 0.143 | 0.4183 | 0.1092 | 0.3938 | 0.3119 | 0.4636 |
| No log | 4.0 | 428 | 12.8750 | 0.2236 | 0.4139 | 0.218 | 0.12 | 0.1699 | 0.4095 | 0.225 | 0.4324 | 0.5089 | 0.296 | 0.4525 | 0.7051 | 0.3626 | 0.6342 | 0.0964 | 0.5253 | 0.117 | 0.3996 | 0.2042 | 0.4631 | 0.3377 | 0.5222 |
| 90.5185 | 5.0 | 535 | 11.9853 | 0.2701 | 0.4731 | 0.2752 | 0.192 | 0.1984 | 0.475 | 0.2573 | 0.4629 | 0.5406 | 0.357 | 0.4739 | 0.7304 | 0.4639 | 0.6973 | 0.1397 | 0.5443 | 0.2001 | 0.5134 | 0.2089 | 0.4354 | 0.3381 | 0.5124 |
| 90.5185 | 6.0 | 642 | 12.6566 | 0.2422 | 0.4501 | 0.2296 | 0.2014 | 0.1863 | 0.425 | 0.2339 | 0.4469 | 0.5379 | 0.3612 | 0.4893 | 0.7289 | 0.3361 | 0.5752 | 0.1231 | 0.5329 | 0.1813 | 0.5272 | 0.2314 | 0.5108 | 0.3393 | 0.5436 |
| 90.5185 | 7.0 | 749 | 12.7385 | 0.2411 | 0.432 | 0.2334 | 0.1769 | 0.1784 | 0.442 | 0.2291 | 0.4407 | 0.5321 | 0.3208 | 0.4863 | 0.7248 | 0.3662 | 0.6527 | 0.115 | 0.5114 | 0.1671 | 0.4969 | 0.2244 | 0.4677 | 0.3328 | 0.532 |
| 90.5185 | 8.0 | 856 | 12.8410 | 0.2614 | 0.4702 | 0.2516 | 0.1796 | 0.1916 | 0.4767 | 0.2389 | 0.451 | 0.5373 | 0.3511 | 0.4776 | 0.7404 | 0.3826 | 0.6739 | 0.1451 | 0.5456 | 0.2148 | 0.5022 | 0.2567 | 0.4646 | 0.3078 | 0.5 |
| 90.5185 | 9.0 | 963 | 13.1283 | 0.1857 | 0.3361 | 0.1772 | 0.1922 | 0.1448 | 0.3403 | 0.2197 | 0.4346 | 0.5488 | 0.368 | 0.5015 | 0.7352 | 0.2542 | 0.6599 | 0.0948 | 0.5392 | 0.0841 | 0.5022 | 0.211 | 0.5062 | 0.2846 | 0.5364 |
| 13.6999 | 10.0 | 1070 | 12.8353 | 0.2457 | 0.4365 | 0.2273 | 0.1837 | 0.1881 | 0.4385 | 0.2388 | 0.4518 | 0.5494 | 0.3529 | 0.4936 | 0.7493 | 0.3722 | 0.6748 | 0.1472 | 0.5671 | 0.1703 | 0.496 | 0.2429 | 0.4831 | 0.296 | 0.5262 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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