rtdetr-v2-r50-cppe5-finetune-2

ranm26/rtdetr-v2-r50-cppe5-finetune-2

rtdetr-v2-r50-cppe5-finetune-2 is a object detection model from ranm26. Use it when you need objects located in an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

11% of all-time downloads

All-time downloads

Public

Parameters

42.9M

172 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors172 MB · 100%

At a glance

Task: Object Detection
Library: transformers
License: apache-2.0
Model type: rt_detr_v2
Access: Public
Created: Nov 11, 2025
Updated: Nov 11, 2025
SHA: f6965f22

Base models

PekingU/rtdetr_v2_r50vd

Model card

From the Hugging Face model README

rtdetr-v2-r50-cppe5-finetune-2

This model is a fine-tuned version of PekingU/rtdetr_v2_r50vd on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 6.6493
Map: 0.6094
Mar 100: 0.7099
Map 50: 0.9567
Map 75: 0.719

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: linear
lr_scheduler_warmup_steps: 300
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Mar 100	Map 50	Map 75
No log	1.0	142	34.3182	0.0607	0.6404	0.094	0.0739
No log	2.0	284	8.2558	0.4949	0.7404	0.8746	0.5321
No log	3.0	426	7.6811	0.596	0.7113	0.9488	0.7037
175.7115	4.0	568	6.7879	0.5943	0.7057	0.9781	0.7188
175.7115	5.0	710	6.6212	0.6087	0.7248	0.9704	0.7148
175.7115	6.0	852	6.6538	0.5936	0.7255	0.972	0.7068
175.7115	7.0	994	6.5767	0.6078	0.7298	0.9675	0.7592
12.1686	8.0	1136	6.6338	0.6246	0.7511	0.9646	0.7952
12.1686	9.0	1278	6.5246	0.598	0.7262	0.9483	0.7194
12.1686	10.0	1420	6.3852	0.6277	0.7369	0.959	0.8146
11.266	11.0	1562	6.6311	0.6092	0.7312	0.9659	0.7514
11.266	12.0	1704	6.4214	0.609	0.7333	0.9642	0.7471
11.266	13.0	1846	6.4222	0.6219	0.7319	0.9696	0.7763
11.266	14.0	1988	6.5066	0.617	0.7426	0.9636	0.7628
10.6436	15.0	2130	6.5157	0.6119	0.7248	0.9767	0.79
10.6436	16.0	2272	6.4737	0.6119	0.7348	0.9571	0.7829
10.6436	17.0	2414	6.5789	0.6326	0.7277	0.9674	0.7798
10.0889	18.0	2556	6.5001	0.6168	0.722	0.9755	0.7703
10.0889	19.0	2698	6.4702	0.614	0.7326	0.963	0.7387
10.0889	20.0	2840	6.5242	0.6151	0.7248	0.9673	0.7568
10.0889	21.0	2982	6.5797	0.6293	0.7298	0.9738	0.7369
9.4174	22.0	3124	6.5303	0.616	0.7355	0.9669	0.7879
9.4174	23.0	3266	6.7147	0.6079	0.7262	0.9668	0.756
9.4174	24.0	3408	6.6836	0.6146	0.7319	0.9725	0.7951
8.9177	25.0	3550	6.6182	0.6048	0.7298	0.9734	0.7162
8.9177	26.0	3692	6.5351	0.6182	0.7156	0.9713	0.7856
8.9177	27.0	3834	6.3831	0.6235	0.7262	0.9782	0.8026
8.9177	28.0	3976	6.4694	0.6194	0.7326	0.9756	0.7649
8.4449	29.0	4118	6.6127	0.6119	0.717	0.9672	0.7576
8.4449	30.0	4260	6.6870	0.6078	0.7312	0.9562	0.7143
8.4449	31.0	4402	6.7105	0.6084	0.7163	0.9659	0.7379
7.9999	32.0	4544	6.6299	0.6091	0.717	0.9607	0.7731
7.9999	33.0	4686	6.7453	0.6062	0.7262	0.9625	0.7409
7.9999	34.0	4828	6.6493	0.6121	0.7191	0.9643	0.7963
7.9999	35.0	4970	6.8267	0.6044	0.7213	0.9668	0.7582
7.5518	36.0	5112	6.8738	0.604	0.7156	0.9669	0.735
7.5518	37.0	5254	6.8444	0.6068	0.7113	0.967	0.7484
7.5518	38.0	5396	6.8525	0.605	0.7142	0.9667	0.7401
7.1858	39.0	5538	6.8547	0.609	0.7149	0.9683	0.7406
7.1858	40.0	5680	6.8616	0.6103	0.7156	0.9697	0.7328

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu128
Datasets 4.4.1
Tokenizers 0.22.1

Task: Object Detection
Library: transformers
Type: rt_detr_v2
License: apache-2.0
Created: Nov 11, 2025
Updated: Nov 11, 2025