detr_finetuned_cppe5

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1933
• Map: 0.0
• Map 50: 0.0
• Map 75: 0.0
• Map Small: 0.0
• Map Medium: -1.0
• Map Large: -1.0
• Mar 1: 0.0
• Mar 10: 0.0
• Mar 100: 0.0
• Mar Small: 0.0
• Mar Medium: -1.0
• Mar Large: -1.0
• Map Coverall: 0.0
• Mar 100 Coverall: 0.0
• Map Face Shield: 0.0
• Mar 100 Face Shield: 0.0
• Map Gloves: 0.0
• Mar 100 Gloves: 0.0
• Map Goggles: 0.0
• Mar 100 Goggles: 0.0
• Map Mask: 0.0
• Mar 100 Mask: 0.0

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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• num_epochs: 30

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	1.7858	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
No log	2.0	426	1.7974	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2.612	3.0	639	1.6086	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2.612	4.0	852	1.5644	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.3972	5.0	1065	1.4356	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.3972	6.0	1278	1.4547	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.3972	7.0	1491	1.4207	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.2125	8.0	1704	1.3967	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.2125	9.0	1917	1.3162	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.09	10.0	2130	1.3086	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1.09	11.0	2343	1.3013	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.9743	12.0	2556	1.2823	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.9743	13.0	2769	1.2798	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.9743	14.0	2982	1.2379	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.8793	15.0	3195	1.2404	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.8793	16.0	3408	1.2136	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.7806	17.0	3621	1.2239	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.7806	18.0	3834	1.2372	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.7053	19.0	4047	1.2269	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.7053	20.0	4260	1.2231	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.7053	21.0	4473	1.2135	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.6369	22.0	4686	1.2037	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.6369	23.0	4899	1.2048	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5831	24.0	5112	1.1930	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5831	25.0	5325	1.2022	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5447	26.0	5538	1.1945	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5447	27.0	5751	1.1970	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5447	28.0	5964	1.1923	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5184	29.0	6177	1.1936	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.5184	30.0	6390	1.1933	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

Framework versions

• Transformers 4.46.0
• Pytorch 2.2.2
• Datasets 3.0.2
• Tokenizers 0.20.1