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configs/msrs_b2.toml

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+# RTFDNet Training Config — FMB dataset, MiT-B2 backbone
+# Paper: RTFDNet (ArXiv 2603.09149)
+
+[model]
+variant = "mit_b2"
+channels = 256
+pretrained = "models/mit_b2.pth"
+drop_path_rate = 0.1
+dropout_ratio = 0.1
+gradient_checkpointing = false
+
+[data]
+dataset = "msrs"
+data_root = "data/ade_msrs"
+num_classes = 9
+crop_size = [480, 640]
+num_workers = 4
+pin_memory = true
+
+[training]
+batch_size = "auto"
+learning_rate = 3e-5
+weight_decay = 0.01
+optimizer = "adamw"
+betas = [0.9, 0.999]
+max_epochs = 300
+precision = "fp16"
+gradient_accumulation = 1
+max_grad_norm = 1.0
+seed = 42
+head_lr_mult = 10.0
+
+[scheduler]
+type = "warmup_cosine"
+warmup_ratio = 0.05
+min_lr = 1e-5
+T_max = 5
+
+[losses]
+ce_weight = 0.5
+modal_ce_weight = 1.0
+akd_weight = 0.5
+region_l1_weight = 1.0
+
+[checkpoint]
+save_every_n_epochs = 10
+keep_top_k = 2
+metric = "mIoU"
+mode = "max"
+
+[early_stopping]
+enabled = true
+patience = 30
+min_delta = 0.001
+
+[validation]
+interval = 5