learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: cosine
lr_scheduler_warmup_steps: 0.05
num_epochs: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Map	Map50	Map75	Mar 100	Accuracy
1031.1965	1.0	36	361.7602	0.0	0.0	0.0	0.0	0.0
369.9709	2.0	72	70.0161	0.0	0.0	0.0	0.0	0.0
56.7635	3.0	108	31.5820	0.0	0.0	0.0	0.0	0.0
36.0670	4.0	144	17.0780	0.1443	0.2178	0.1774	0.1511	0.2113
19.3787	5.0	180	12.0425	0.5076	0.7834	0.6345	0.5716	0.7012
16.8609	6.0	216	8.7856	0.5603	0.8918	0.6509	0.6163	0.8355
13.9387	7.0	252	7.7601	0.5725	0.9052	0.6853	0.634	0.8716
13.4897	8.0	288	7.9862	0.5758	0.9275	0.7017	0.6504	0.8693
13.1799	9.0	324	7.4389	0.5952	0.9048	0.7377	0.6496	0.86
12.3844	10.0	360	7.2910	0.6127	0.9426	0.7271	0.6752	0.871
12.3269	11.0	396	7.3734	0.6219	0.9454	0.7722	0.6738	0.8824
11.9732	12.0	432	7.2280	0.6079	0.9246	0.7294	0.6631	0.8627
11.8941	13.0	468	7.1169	0.6139	0.9465	0.7341	0.6702	0.8874
11.7684	14.0	504	7.1686	0.6108	0.9412	0.7197	0.6709	0.8701
11.6225	15.0	540	7.1556	0.6102	0.9373	0.7129	0.6667	0.8808

ranm26/rtdetr-v2-r50-lpph-finetune-improved-v4

rtdetr-v2-r50-lpph-finetune-improved-v4