learning_rate: 6e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Mean Accuracy	Overall Accuracy	Per Category Iou	Per Category Accuracy
0.0176	12.1951	1000	0.0153	0.4991	0.5001	0.9978	[0.9978437819175541, 0.00041657987919183504]	[0.9997885648043022, 0.00046175157765122367]
0.0173	24.3902	2000	0.0153	0.4991	0.5001	0.9978	[0.9978095148690534, 0.0004100657472081357]	[0.999754230969827, 0.00046175157765122367]
0.0144	36.5854	3000	0.0146	0.4991	0.5001	0.9980	[0.9979986133831826, 0.00026932399676811203]	[0.9999440574585123, 0.00027705094659073417]
0.0208	48.7805	4000	0.0151	0.4992	0.5002	0.9980	[0.9979567074182948, 0.0004395926441497546]	[0.9999017103951866, 0.00046175157765122367]

whyoke/segmentation_model_50ep_2

segmentation_model_50ep_2