ExamInk-Seg / config.json
ljj
feat: init
1b0973e
{
"architectures": [
"InkEraserModel"
],
"model_type": "unet_plus_plus",
"encoder_name": "resnet50",
"encoder_weights": "imagenet",
"in_channels": 3,
"classes": 1,
"decoder_attention_type": "scse",
"activation": "sigmoid",
"framework": "pytorch-lightning",
"task": "binary-segmentation",
"input_normalization": {
"mean": [
0.485,
0.456,
0.406
],
"std": [
0.229,
0.224,
0.225
],
"max_pixel_value": 255.0
},
"training_config": {
"optimizer": "AdamW",
"lr": 3e-05,
"weight_decay": 1e-05,
"loss": {
"dice_weight": 0.8,
"bce_weight": 0.2,
"bce_pos_weight": 2.0,
"dice_from_logits": true
},
"metrics": [
"iou_03",
"iou_05",
"f1_03",
"f1_05"
],
"scheduler": {
"name": "ReduceLROnPlateau",
"mode": "max",
"monitor": "val_iou_05",
"factor": 0.5,
"patience": 2,
"min_lr": 1e-07
},
"train": {
"batch_size": 6,
"crop_size": 1024,
"accumulate_grad_batches": 4,
"precision": "bf16-mixed",
"max_epochs": 200,
"min_epochs": 5
}
},
"inference": {
"sliding_window": {
"tile": 1024,
"stride": 768,
"tta_hflip": true
}
},
"description": "ExamInk-Seg 二值墨迹分割模型(U-Net++ + ResNet50 编码器)。",
"license": "MIT"
}