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---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_r50vd
tags:
- object-detection
- vision
- generated_from_trainer
model-index:
- name: suas-2025-rtdetr-finetuned
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. -->
# suas-2025-rtdetr-finetuned
This model is a fine-tuned version of [PekingU/rtdetr_r50vd](https://huggingface.co/PekingU/rtdetr_r50vd) on the mfly-auton/suas-2025-synthetic-data dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8868
- Map: 0.8924
- Map 50: 0.9568
- Map 75: 0.9554
- Map Small: 0.8115
- Map Medium: 0.9048
- Map Large: 0.9511
- Mar 1: 0.8296
- Mar 10: 0.938
- Mar 100: 0.9407
- Mar Small: 0.8752
- Mar Medium: 0.9535
- Mar Large: 0.9911
- Map Baseball-bat: 0.8962
- Mar 100 Baseball-bat: 0.9382
- Map Basketball: 0.8344
- Mar 100 Basketball: 0.9077
- Map Car: -1.0
- Mar 100 Car: -1.0
- Map Football: 0.814
- Mar 100 Football: 0.8709
- Map Human: 0.9172
- Mar 100 Human: 0.9686
- Map Luggage: 0.8623
- Mar 100 Luggage: 0.9241
- Map Mattress: 0.9809
- Mar 100 Mattress: 0.9971
- Map Motorcycle: 0.9393
- Mar 100 Motorcycle: 0.9751
- Map Skis: 0.8496
- Mar 100 Skis: 0.9692
- Map Snowboard: 0.9857
- Mar 100 Snowboard: 0.9947
- Map Soccer-ball: 0.8382
- Mar 100 Soccer-ball: 0.8755
- Map Stop-sign: 0.9735
- Mar 100 Stop-sign: 0.9957
- Map Tennis-racket: 0.9007
- Mar 100 Tennis-racket: 0.9245
- Map Umbrella: 0.8994
- Mar 100 Umbrella: 0.9775
- Map Volleyball: 0.8024
- Mar 100 Volleyball: 0.8507
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
### 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 Baseball-bat | Mar 100 Baseball-bat | Map Basketball | Mar 100 Basketball | Map Car | Mar 100 Car | Map Football | Mar 100 Football | Map Human | Mar 100 Human | Map Luggage | Mar 100 Luggage | Map Mattress | Mar 100 Mattress | Map Motorcycle | Mar 100 Motorcycle | Map Skis | Mar 100 Skis | Map Snowboard | Mar 100 Snowboard | Map Soccer-ball | Mar 100 Soccer-ball | Map Stop-sign | Mar 100 Stop-sign | Map Tennis-racket | Mar 100 Tennis-racket | Map Umbrella | Mar 100 Umbrella | Map Volleyball | Mar 100 Volleyball |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------------:|:--------------------:|:--------------:|:------------------:|:-------:|:-----------:|:------------:|:----------------:|:---------:|:-------------:|:-----------:|:---------------:|:------------:|:----------------:|:--------------:|:------------------:|:--------:|:------------:|:-------------:|:-----------------:|:---------------:|:-------------------:|:-------------:|:-----------------:|:-----------------:|:---------------------:|:------------:|:----------------:|:--------------:|:------------------:|
| 12.0474 | 1.0 | 438 | 5.5119 | 0.8067 | 0.8868 | 0.8817 | 0.7597 | 0.7886 | 0.8834 | 0.7817 | 0.9168 | 0.924 | 0.8348 | 0.9511 | 0.9848 | 0.7992 | 0.9114 | 0.819 | 0.901 | -1.0 | -1.0 | 0.7627 | 0.8381 | 0.6589 | 0.9657 | 0.8118 | 0.9173 | 0.9643 | 0.9961 | 0.8513 | 0.9658 | 0.5388 | 0.9767 | 0.9801 | 0.9925 | 0.7934 | 0.85 | 0.9652 | 0.988 | 0.8307 | 0.9057 | 0.8198 | 0.9603 | 0.6983 | 0.7671 |
| 6.1205 | 2.0 | 876 | 5.0519 | 0.8186 | 0.8885 | 0.8836 | 0.746 | 0.7754 | 0.902 | 0.7791 | 0.9033 | 0.9094 | 0.8072 | 0.9373 | 0.9872 | 0.8735 | 0.9189 | 0.8175 | 0.9172 | -1.0 | -1.0 | 0.7607 | 0.8174 | 0.798 | 0.9653 | 0.8087 | 0.8941 | 0.9531 | 0.9942 | 0.7115 | 0.9665 | 0.7689 | 0.9508 | 0.9767 | 0.9957 | 0.7882 | 0.846 | 0.92 | 0.9799 | 0.8979 | 0.9208 | 0.7901 | 0.9309 | 0.5955 | 0.6338 |
| 5.3217 | 3.0 | 1314 | 4.0739 | 0.8811 | 0.9513 | 0.9499 | 0.7797 | 0.8841 | 0.9549 | 0.8259 | 0.9337 | 0.9374 | 0.8626 | 0.9518 | 0.9937 | 0.8664 | 0.9269 | 0.8426 | 0.9086 | -1.0 | -1.0 | 0.7995 | 0.8595 | 0.891 | 0.9688 | 0.8574 | 0.9292 | 0.9881 | 0.9998 | 0.9232 | 0.9719 | 0.8199 | 0.9958 | 0.9816 | 0.9932 | 0.82 | 0.862 | 0.979 | 0.994 | 0.8971 | 0.9198 | 0.8925 | 0.9689 | 0.777 | 0.8258 |
| 4.7931 | 4.0 | 1752 | 3.8984 | 0.8943 | 0.9605 | 0.9589 | 0.8046 | 0.9139 | 0.9535 | 0.8289 | 0.9363 | 0.9404 | 0.8726 | 0.9571 | 0.9849 | 0.8889 | 0.9341 | 0.8321 | 0.9053 | -1.0 | -1.0 | 0.809 | 0.8622 | 0.9072 | 0.9685 | 0.8876 | 0.9389 | 0.9796 | 0.9993 | 0.9379 | 0.9757 | 0.8801 | 0.96 | 0.9855 | 0.9972 | 0.8379 | 0.8745 | 0.9811 | 0.994 | 0.9046 | 0.9302 | 0.8907 | 0.9722 | 0.7979 | 0.8531 |
| 4.634 | 5.0 | 2190 | 3.8868 | 0.8924 | 0.9568 | 0.9554 | 0.8115 | 0.9048 | 0.9511 | 0.8296 | 0.938 | 0.9407 | 0.8752 | 0.9535 | 0.9911 | 0.8962 | 0.9382 | 0.8344 | 0.9077 | -1.0 | -1.0 | 0.814 | 0.8709 | 0.9172 | 0.9686 | 0.8623 | 0.9241 | 0.9809 | 0.9971 | 0.9393 | 0.9751 | 0.8496 | 0.9692 | 0.9857 | 0.9947 | 0.8382 | 0.8755 | 0.9735 | 0.9957 | 0.9007 | 0.9245 | 0.8994 | 0.9775 | 0.8024 | 0.8507 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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