---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_r18vd_coco_o365
tags:
- generated_from_trainer
model-index:
- name: kvasir_seg_rtdetr_r18_test_fps
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# kvasir_seg_rtdetr_r18_test_fps

This model is a fine-tuned version of [PekingU/rtdetr_r18vd_coco_o365](https://huggingface.co/PekingU/rtdetr_r18vd_coco_o365) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.4708
- Map: 0.5375
- Map 50: 0.7037
- Map 75: 0.6008
- Map Small: 0.0
- Map Medium: 0.2762
- Map Large: 0.5563
- Mar 1: 0.6024
- Mar 10: 0.8218
- Mar 100: 0.9209
- Mar Small: 0.0
- Mar Medium: 0.78
- Mar Large: 0.9325
- Map Polyp: 0.5375
- Mar 100 Polyp: 0.9209

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- 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 Polyp | Mar 100 Polyp |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|
| 188.8938      | 1.0   | 100  | 35.3914         | 0.045  | 0.0921 | 0.0405 | 0.0       | 0.0001     | 0.0612    | 0.1175 | 0.3521 | 0.6398  | 0.0       | 0.09       | 0.6705    | 0.045     | 0.6398        |
| 20.5545       | 2.0   | 200  | 13.3860         | 0.0707 | 0.1207 | 0.0633 | 0.0       | 0.0164     | 0.0763    | 0.2    | 0.5607 | 0.8398  | 0.0       | 0.63       | 0.8545    | 0.0707    | 0.8398        |
| 12.8462       | 3.0   | 300  | 8.8009          | 0.251  | 0.3922 | 0.2349 | 0.0       | 0.1155     | 0.263     | 0.3758 | 0.7171 | 0.8782  | 0.0       | 0.71       | 0.891     | 0.251     | 0.8782        |
| 11.3          | 4.0   | 400  | 8.9424          | 0.2968 | 0.4137 | 0.3193 | 0.0       | 0.2263     | 0.3046    | 0.3929 | 0.7687 | 0.9038  | 0.0       | 0.77       | 0.915     | 0.2968    | 0.9038        |
| 10.3262       | 5.0   | 500  | 7.8881          | 0.2819 | 0.4434 | 0.3041 | 0.0       | 0.2255     | 0.2897    | 0.4223 | 0.7374 | 0.8839  | 0.0       | 0.57       | 0.904     | 0.2819    | 0.8839        |
| 9.4336        | 6.0   | 600  | 7.9411          | 0.3048 | 0.4533 | 0.3209 | 0.0       | 0.2202     | 0.3159    | 0.4649 | 0.7934 | 0.9024  | 0.0       | 0.76       | 0.914     | 0.3048    | 0.9024        |
| 8.996         | 7.0   | 700  | 7.2079          | 0.4942 | 0.6964 | 0.5359 | 0.0       | 0.2982     | 0.5086    | 0.5531 | 0.7995 | 0.9171  | 0.0       | 0.74       | 0.9305    | 0.4942    | 0.9171        |
| 8.3482        | 8.0   | 800  | 6.5042          | 0.4987 | 0.6906 | 0.5471 | 0.0       | 0.2387     | 0.5154    | 0.5768 | 0.8095 | 0.9095  | 0.0       | 0.75       | 0.922     | 0.4987    | 0.9095        |
| 7.9702        | 9.0   | 900  | 6.4708          | 0.5375 | 0.7037 | 0.6008 | 0.0       | 0.2762     | 0.5563    | 0.6024 | 0.8218 | 0.9209  | 0.0       | 0.78       | 0.9325    | 0.5375    | 0.9209        |
| 7.7992        | 10.0  | 1000 | 6.3745          | 0.5317 | 0.7162 | 0.5988 | 0.0       | 0.2473     | 0.551     | 0.5953 | 0.8299 | 0.9223  | 0.0       | 0.76       | 0.935     | 0.5317    | 0.9223        |


### Framework versions

- Transformers 4.53.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1