learning_rate: 0.0001
train_batch_size: 16
eval_batch_size: 16
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: 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
125.6384	1.0	50	37.6923	0.0834	0.1442	0.0839	0.0	0.0079	0.0865	0.1363	0.2933	0.2999	0.0	0.0216	0.3163	0.2779	0.5539	0.1123	0.3765	0.0014	0.1071	-1.0	-1.0	0.0088	0.1111	0.0961	0.2177	0.0036	0.4333
35.9436	2.0	100	15.1525	0.3763	0.5266	0.4267	0.0	0.0352	0.4024	0.433	0.576	0.6206	0.0	0.1375	0.6705	0.6674	0.8007	0.4107	0.7647	0.1191	0.5286	-1.0	-1.0	0.1109	0.4	0.4515	0.6965	0.498	0.5333
21.7112	3.0	150	11.2377	0.476	0.6327	0.5326	0.0208	0.3131	0.5013	0.485	0.697	0.7371	0.1	0.5119	0.7757	0.7563	0.8539	0.5948	0.802	0.1158	0.6286	-1.0	-1.0	0.1742	0.5056	0.6452	0.7991	0.5699	0.8333
17.6387	4.0	200	10.1056	0.5144	0.6638	0.5723	0.0406	0.304	0.5379	0.5509	0.7315	0.7734	0.25	0.575	0.8052	0.7854	0.8759	0.5764	0.8078	0.1273	0.6786	-1.0	-1.0	0.1969	0.5861	0.6409	0.792	0.7596	0.9
15.7398	5.0	250	9.5453	0.5128	0.6793	0.5766	0.1021	0.2854	0.5362	0.563	0.7215	0.7592	0.3	0.5494	0.7934	0.7967	0.8766	0.5882	0.8127	0.1308	0.6357	-1.0	-1.0	0.2046	0.6042	0.6572	0.7929	0.699	0.8333
14.3980	6.0	300	9.4995	0.5285	0.6899	0.588	0.0708	0.3182	0.5561	0.5619	0.7537	0.7736	0.3	0.5562	0.8106	0.7968	0.8773	0.5852	0.8108	0.1779	0.6857	-1.0	-1.0	0.2146	0.6125	0.6377	0.7885	0.7586	0.8667
13.5016	7.0	350	9.3702	0.5644	0.7296	0.6263	0.0839	0.2914	0.5951	0.586	0.7588	0.7791	0.3	0.5528	0.8173	0.8052	0.873	0.5996	0.8059	0.2201	0.6857	-1.0	-1.0	0.2289	0.6222	0.6328	0.7876	0.9	0.9
12.7463	8.0	400	9.4010	0.5326	0.6996	0.5913	0.0503	0.3078	0.5617	0.5723	0.7403	0.7648	0.3	0.5585	0.7988	0.8039	0.8773	0.576	0.7902	0.213	0.6714	-1.0	-1.0	0.2183	0.5958	0.6256	0.7876	0.7586	0.8667
12.3229	9.0	450	9.4434	0.5513	0.7262	0.62	0.0505	0.2788	0.582	0.5866	0.7457	0.7747	0.3	0.5642	0.8114	0.7968	0.8681	0.5797	0.7922	0.2169	0.7214	-1.0	-1.0	0.2352	0.6111	0.6131	0.7885	0.8663	0.8667
12.0052	10.0	500	9.4528	0.5391	0.7098	0.6025	0.0504	0.294	0.5687	0.5733	0.7379	0.7658	0.3	0.5784	0.7963	0.8019	0.873	0.5721	0.7882	0.2104	0.6714	-1.0	-1.0	0.2356	0.6125	0.6156	0.7832	0.799	0.8667

Framework versions

Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Starmaster7/rt_detrv2_finetuned_trashify_box_detector_v1

rt_detrv2_finetuned_trashify_box_detector_v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Starmaster7/
rt_detrv2_finetuned_trashify_box_detector_v1