learning_rate: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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 100 Bin	Map Hand	Mar 100 Hand	Map Not Bin	Mar 100 Not Bin	Map Not Hand	Mar 100 Not Hand	Map Not Trash	Mar 100 Not Trash	Map Trash	Mar 100 Trash	Map Trash Arm	Mar 100 Trash Arm
27.0463	1.0	50	15.4899	0.2705	0.3893	0.3055	0.025	0.069	0.2829	0.3481	0.4969	0.5391	0.05	0.2489	0.5863	0.5869	0.8454	0.4955	0.8127	0.0302	0.2571	-1.0	-1.0	0.1072	0.5222	0.4033	0.7973	0.0	0.0
17.6579	2.0	100	10.9661	0.3346	0.4669	0.3667	0.03	0.1191	0.3575	0.4088	0.6023	0.6583	0.15	0.5443	0.6936	0.6209	0.861	0.599	0.8225	0.021	0.5929	-1.0	-1.0	0.1927	0.5778	0.5731	0.7956	0.0011	0.3
16.5296	3.0	150	10.3041	0.3775	0.5146	0.4155	0.0667	0.1784	0.4033	0.4356	0.6377	0.7523	0.2	0.6085	0.7844	0.6671	0.8631	0.6256	0.8157	0.1035	0.6857	-1.0	-1.0	0.2509	0.6222	0.6036	0.7938	0.0144	0.7333
14.5736	4.0	200	9.8255	0.4818	0.657	0.549	0.0755	0.2824	0.5048	0.5649	0.7088	0.7488	0.2	0.5443	0.778	0.7252	0.883	0.6404	0.8196	0.1572	0.6	-1.0	-1.0	0.2568	0.5931	0.6036	0.7973	0.5079	0.8
20.2668	5.0	250	9.3334	0.4665	0.6285	0.5347	0.075	0.2033	0.4919	0.5653	0.7297	0.7619	0.15	0.571	0.787	0.7351	0.8844	0.6281	0.8157	0.1393	0.6429	-1.0	-1.0	0.2829	0.5944	0.6447	0.8009	0.3688	0.8333
14.1717	6.0	300	9.3199	0.503	0.6946	0.5887	0.075	0.212	0.5296	0.5867	0.7173	0.7627	0.15	0.6483	0.7833	0.7582	0.883	0.6176	0.8098	0.1768	0.7	-1.0	-1.0	0.3005	0.6139	0.6129	0.8027	0.5519	0.7667
11.9656	7.0	350	9.4737	0.5183	0.6964	0.5876	0.15	0.2405	0.5445	0.5575	0.7217	0.7499	0.15	0.5625	0.7792	0.7627	0.8801	0.5878	0.8088	0.1316	0.6071	-1.0	-1.0	0.282	0.5903	0.5958	0.7796	0.7495	0.8333
11.6564	8.0	400	9.5291	0.5383	0.7383	0.6282	0.0333	0.2741	0.565	0.5691	0.7143	0.748	0.1	0.5602	0.7749	0.7843	0.8844	0.6005	0.8	0.1929	0.6214	-1.0	-1.0	0.265	0.5944	0.626	0.7876	0.7611	0.8
11.7354	9.0	450	9.5637	0.5305	0.7275	0.6076	0.05	0.279	0.5548	0.5522	0.6963	0.7329	0.15	0.5511	0.7581	0.7739	0.8787	0.5924	0.798	0.1512	0.5357	-1.0	-1.0	0.2765	0.6	0.6277	0.785	0.7611	0.8
8.5063	10.0	500	9.6423	0.5227	0.7138	0.5941	0.05	0.2718	0.5486	0.5579	0.7102	0.7442	0.15	0.5659	0.7689	0.7657	0.8816	0.6027	0.7951	0.1553	0.6286	-1.0	-1.0	0.2737	0.5917	0.6143	0.7681	0.7248	0.8

Framework versions

Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 4.5.0
Tokenizers 0.22.2

Quantum-Monk/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

Quantum-Monk/
rt_detrv2_finetuned_trashify_box_detector_v1