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Pranilllllll/
geonusaf-unetformer-r18-random-fold0

Name: geonusaf-unetformer-r18-random-fold0
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GeoNUSAF - UNetFormer (ResNet-18) - random split, fold 0

Kathmandu Valley land-use segmentation, 6 classes, ignore_index=255.

field	value
architecture	UNetFormer, timm resnet18 encoder (ImageNet), global-local attention decoder
arch version	unetformer-r18-v2 (sig 29554ac657c8)
split mode	random
fold	0 of 3
seed	42
input	512x512, ImageNet norm, effective GSD 0.586 m/px
classes	Residential, Road, River, Forest, UnusedLand, Agricultural
lr (dec/enc)	0.0003 / 3e-05, AdamW wd 0.01
schedule	500-step warmup, cosine over 120 epochs
regularization	EMA 0.999, label smoothing 0.05, drop path 0.1, dropout 0.1
aux head weight	0.4
weights	EMA
best epoch	118
val mIoU	0.5263
val mF1	0.6776
val OA	0.7893
val kappa	0.6667

Split caveat: block is sequence-block CV using an export-order proxy, not spatial CV.

LR deviates from the UNetFormer paper's 6e-4 (reduced to 3e-4 for parity with the other baselines at this dataset scale).

Architecture is an independent implementation of Wang et al. (2022), ISPRS J. Photogramm. Remote Sens. 190:196-214 (the reference repo is GPL-3.0).

Checkpoint best.pt holds model_state (EMA weights) plus cfg, metrics, arch_sig.