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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