learning_rate: 0.0001
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_ratio: 0.05
num_epochs: 10
mixed_precision_training: Native AMP

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 Bin	Mar Bin	Map Hand	Mar Hand	Map Not Bin	Mar Not Bin	Map Not Hand	Mar Not Hand	Map Not Trash	Mar Not Trash	Map Trash	Mar Trash	Map Trash Arm	Mar Trash Arm
10.8388	1.0	99	9.1499	0.5045	0.6872	0.5749	0.075	0.3381	0.5344	0.5451	0.7097	0.7405	0.3	0.5085	0.7778	0.7808	0.8936	0.5858	0.7676	0.2115	0.6214	-1.0	-1.0	0.187	0.5736	0.6221	0.7867	0.6396	0.8
10.9884	2.0	198	9.2812	0.5164	0.6955	0.5818	0.1252	0.3818	0.5409	0.5497	0.7213	0.7607	0.45	0.5551	0.7949	0.7887	0.8879	0.5401	0.7657	0.1966	0.6929	-1.0	-1.0	0.1767	0.5653	0.6468	0.7858	0.7496	0.8667
10.4912	3.0	297	9.1873	0.5412	0.7153	0.6217	0.0026	0.3043	0.5761	0.5626	0.7161	0.7461	0.75	0.5006	0.7839	0.8086	0.8816	0.5516	0.7706	0.1984	0.6286	-1.0	-1.0	0.2276	0.5722	0.6494	0.7903	0.8112	0.8333
9.8673	4.0	396	9.3256	0.5031	0.712	0.5252	0.0625	0.3918	0.5343	0.5311	0.6931	0.7153	0.25	0.5659	0.7443	0.7747	0.861	0.5995	0.7814	0.255	0.6	-1.0	-1.0	0.1833	0.5403	0.6308	0.7761	0.5755	0.7333
9.2601	5.0	495	9.1876	0.5416	0.7069	0.6206	0.0	0.2878	0.5748	0.5615	0.6971	0.7348	0.0	0.4886	0.7725	0.7915	0.8787	0.6167	0.7775	0.1929	0.5929	-1.0	-1.0	0.2168	0.4958	0.6825	0.7973	0.7494	0.8667
8.7615	6.0	594	9.3623	0.5296	0.7233	0.5813	0.1253	0.4046	0.5575	0.5624	0.7136	0.7385	0.55	0.5335	0.7687	0.7859	0.878	0.5734	0.7588	0.2579	0.6286	-1.0	-1.0	0.2249	0.5403	0.6609	0.792	0.6744	0.8333
8.231	7.0	693	9.3799	0.5299	0.7049	0.5974	0.0025	0.3827	0.5608	0.5483	0.6916	0.7336	0.15	0.542	0.7674	0.7994	0.8816	0.567	0.7363	0.1994	0.6	-1.0	-1.0	0.2014	0.4986	0.6632	0.785	0.749	0.9
7.7591	8.0	792	9.3271	0.5383	0.7195	0.6136	0.0035	0.3713	0.5717	0.5623	0.7096	0.731	0.25	0.4949	0.7695	0.8092	0.8851	0.5745	0.7402	0.2006	0.6357	-1.0	-1.0	0.2231	0.475	0.6738	0.7832	0.7488	0.8667
7.308	9.0	891	9.2643	0.54	0.7126	0.6163	0.0	0.3795	0.5732	0.568	0.689	0.7346	0.0	0.5193	0.7689	0.7914	0.8823	0.5983	0.7627	0.1941	0.6214	-1.0	-1.0	0.2148	0.4472	0.6672	0.7938	0.7741	0.9
6.8853	10.0	990	9.3215	0.5456	0.7136	0.6227	0.0	0.3711	0.5802	0.5722	0.6935	0.7285	0.0	0.5068	0.7622	0.8005	0.8823	0.5902	0.7539	0.1962	0.6071	-1.0	-1.0	0.2211	0.4389	0.6667	0.7885	0.7991	0.9

Framework versions

Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.5.0
Tokenizers 0.22.2

Kelmoir/rtdetrv2_finetuned_trashify_box_detector_v1

rtdetrv2_finetuned_trashify_box_detector_v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Kelmoir/
rtdetrv2_finetuned_trashify_box_detector_v1