rtdetr-v2-r50-cppe5-finetune-2 – AI Model by greens229 | AlphaNeural AI

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greens229/
rtdetr-v2-r50-cppe5-finetune-2

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object-detection

generated_from_trainer

PekingU/rtdetr_v2_r50vd

endpoints_compatible

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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: 17.0789
Map: 0.1629
Map 50: 0.2497
Map 75: 0.158
Map Small: 0.0436
Map Medium: 0.0817
Map Large: 0.2721
Mar 1: 0.2131
Mar 10: 0.4365
Mar 100: 0.527
Mar Small: 0.1714
Mar Medium: 0.4158
Mar Large: 0.7652
Map Coverall: 0.4861
Mar 100 Coverall: 0.7923
Map Face Shield: 0.0563
Mar 100 Face Shield: 0.5765
Map Gloves: 0.1063
Mar 100 Gloves: 0.4034
Map Goggles: 0.0087
Mar 100 Goggles: 0.3
Map Mask: 0.157
Mar 100 Mask: 0.5627

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: 4
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1

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	213	18.1838	0.1497	0.2559	0.1459	0.036	0.0844	0.2013	0.173	0.36	0.4261	0.1614	0.386	0.6847	0.5054	0.7279	0.0346	0.3633	0.0621	0.2812	0.0051	0.3	0.1412	0.4582

Framework versions

Transformers 4.53.0
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.2