learning_rate: 5e-05
train_batch_size: 8
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: 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 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	107	21.6622	0.0574	0.1029	0.0519	0.0001	0.0074	0.0702	0.0808	0.1764	0.2386	0.0255	0.1314	0.3738	0.263	0.6131	0.0098	0.1962	0.0056	0.1446	0.0002	0.0692	0.0085	0.1698
No log	2.0	214	12.3093	0.1473	0.2769	0.1347	0.04	0.108	0.2006	0.1941	0.3837	0.4464	0.1571	0.3411	0.6232	0.3946	0.6973	0.0871	0.438	0.067	0.392	0.0198	0.3308	0.1682	0.3742
No log	3.0	321	9.8181	0.2151	0.3903	0.2003	0.0862	0.1856	0.2692	0.2513	0.4746	0.5437	0.2899	0.4531	0.6932	0.4504	0.7221	0.1277	0.5734	0.1439	0.471	0.0493	0.4523	0.304	0.4996
No log	4.0	428	9.0262	0.2471	0.44	0.2372	0.0808	0.2084	0.3213	0.2685	0.4722	0.5494	0.2294	0.4611	0.7006	0.5037	0.7387	0.147	0.5823	0.2081	0.4938	0.0661	0.4338	0.3107	0.4982
27.2158	5.0	535	8.6126	0.276	0.4857	0.2769	0.104	0.2124	0.3508	0.2741	0.4908	0.5667	0.3254	0.4704	0.6999	0.5335	0.7261	0.156	0.6139	0.2473	0.5156	0.0958	0.4523	0.3474	0.5253
27.2158	6.0	642	8.4669	0.2826	0.5022	0.2795	0.095	0.2191	0.3575	0.2766	0.4948	0.5704	0.3249	0.461	0.7107	0.5455	0.7356	0.1524	0.6215	0.2571	0.5125	0.1208	0.4646	0.3372	0.5178
27.2158	7.0	749	8.3188	0.3003	0.5202	0.2958	0.1107	0.2348	0.3887	0.2879	0.5044	0.5766	0.3707	0.4823	0.7142	0.5545	0.7288	0.2019	0.6329	0.2655	0.5263	0.1341	0.4631	0.3453	0.532
27.2158	8.0	856	8.3084	0.2972	0.5265	0.2912	0.107	0.2409	0.3732	0.2811	0.5029	0.5811	0.3453	0.4772	0.7138	0.5617	0.7351	0.1649	0.6367	0.2773	0.5192	0.1337	0.4769	0.3485	0.5378
27.2158	9.0	963	8.2764	0.3064	0.5313	0.3049	0.1068	0.2421	0.3871	0.284	0.5073	0.5802	0.373	0.4783	0.7108	0.5621	0.7333	0.182	0.6291	0.2765	0.5299	0.1631	0.4738	0.3483	0.5347
11.8005	10.0	1070	8.3132	0.3055	0.5372	0.3008	0.1094	0.241	0.3888	0.2863	0.4999	0.578	0.3884	0.4832	0.7099	0.5596	0.7275	0.2013	0.6342	0.2742	0.5192	0.146	0.4769	0.3462	0.5324

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.1
Tokenizers 0.21.1

svetadomoi/rtdetr-v2-r34-cppe5-finetune-2

rtdetr-v2-r34-cppe5-finetune-2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

svetadomoi/
rtdetr-v2-r34-cppe5-finetune-2