Add model checkpoints and params

lizard_convnextv2_base/liz_test_param_dict.json

@@ -0,0 +1,4 @@
+{"best_fg_lizard": [0.7, 0.6, 0.6, 0.6, 0.6, 0.5, 0.9],
+"best_seed_lizard": [0.5, 0.6, 0.5, 0.5, 0.7, 0.4, 0.1], 
+"best_fg_f1": [0.6, 0.7, 0.5, 0.4, 0.7, 0.2, 0.1], 
+"best_seed_f1": [0.4, 0.6, 0.5, 0.1, 0.7, 0.4, 0.1]}

lizard_convnextv2_base/mit_test_param_dict.json

@@ -0,0 +1,4 @@
+{"best_fg_lizard": [0.3, 0.6, 0.7, 0.7, 0.4, 0.6, 0.4], 
+"best_seed_lizard": [0.2, 0.6, 0.4, 0.1, 0.2, 0.6, 0.1], 
+"best_fg_f1": [0.2, 0.6, 0.5, 0.4, 0.5, 0.4, 0.5], 
+"best_seed_f1": [0.3, 0.5, 0.4, 0.1, 0.2, 0.5, 0.1]}

lizard_convnextv2_base/params.toml

@@ -0,0 +1,67 @@
+dataset = "lizard"
+data_path_liz = ""
+data_path_mit = ""
+hard_labels = ""
+encoder = "convnextv2_base.fcmae_ft_in22k_in1k"
+out_channels_cls = 8
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.02
+tta = 16
+eval_optim_metric = "mpq"
+n_rounds = 5
+save = false
+f1_metric_ccrop = 248
+match_euc_dist = 6
+eval_criteria = "lizard|alt"
+max_hole_size = 50
+checkpoint_path = ""
+experiment = "convnextv2_base_focal_fulldata_0"
+seed = 42
+fold = 0
+test_as_val = true
+optim_metric = "mpq"
+num_workers = 4
+use_amp = true
+color_scale = 0.2
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

lizard_convnextv2_base/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:149eac1914ef02ba7fe00e26460732695fd2b968a3a43a13d2ce6627b2bbdd71
+size 391626489

lizard_convnextv2_large/liz_test_param_dict.json

@@ -0,0 +1,5 @@
+{"best_fg_lizard": [0.7, 0.6, 0.7, 0.6, 0.6, 0.5, 0.8], 
+"best_seed_lizard": [0.8, 0.6, 0.7, 0.6, 0.4, 0.5, 0.1],
+"best_fg_f1": [0.6, 0.7, 0.3, 0.3, 0.6, 0.2, 0.6],
+"best_seed_f1": [0.9, 0.6, 0.6, 0.3, 0.6, 0.3, 0.1]
+}

lizard_convnextv2_large/mit_test_param_dict.json

@@ -0,0 +1,4 @@
+{"best_fg_lizard": [0.4, 0.6, 0.7, 0.7, 0.5, 0.6, 0.7], 
+"best_seed_lizard": [0.1, 0.6, 0.5, 0.2, 0.3, 0.5, 0.1],
+"best_fg_f1": [0.1, 0.6, 0.4, 0.6, 0.3, 0.4, 0.8], 
+"best_seed_f1": [0.2, 0.6, 0.4, 0.1, 0.2, 0.4, 0.1]}

lizard_convnextv2_large/params.toml

@@ -0,0 +1,67 @@
+dataset = "lizard"
+data_path_liz = ""
+data_path_mit = ""
+hard_labels = ""
+encoder = "convnextv2_large.fcmae_ft_in22k_in1k"
+out_channels_cls = 8
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.02
+tta = 16
+eval_optim_metric = "mpq"
+n_rounds = 5
+save = false
+f1_metric_ccrop = 248
+match_euc_dist = 6
+eval_criteria = "lizard|alt"
+max_hole_size = 50
+checkpoint_path = ""
+experiment = "lizard_convnextv2_large"
+seed = 42
+fold = 0
+test_as_val = true
+optim_metric = "mpq"
+num_workers = 4
+use_amp = true
+color_scale = 0.2
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

lizard_convnextv2_large/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e290320cd4c62954434cf102d2c1c226a2f65ddbbdd457a42ce717f757b3fa83
+size 842160889

lizard_convnextv2_tiny/liz_test_param_dict.json

@@ -0,0 +1,4 @@
+{"best_fg_lizard": [0.5, 0.6, 0.7, 0.6, 0.7, 0.5, 0.7], 
+"best_seed_lizard": [0.2, 0.6, 0.6, 0.2, 0.5, 0.4, 0.1], 
+"best_fg_f1": [0.5, 0.6, 0.5, 0.3, 0.5, 0.3, 0.5],
+"best_seed_f1": [0.2, 0.5, 0.6, 0.1, 0.7, 0.3, 0.1]}

lizard_convnextv2_tiny/mit_test_param_dict.json

@@ -0,0 +1,4 @@
+{"best_fg_lizard": [0.4, 0.7, 0.7, 0.7, 0.5, 0.6, 0.6], 
+"best_seed_lizard": [0.2, 0.6, 0.4, 0.3, 0.2, 0.5, 0.1],
+"best_fg_f1": [0.3, 0.7, 0.5, 0.6, 0.2, 0.5, 0.5],
+"best_seed_f1": [0.2, 0.6, 0.4, 0.3, 0.2, 0.4, 0.1]}

lizard_convnextv2_tiny/params.toml

@@ -0,0 +1,67 @@
+dataset = "lizard"
+data_path_liz = ""
+data_path_mit = ""
+hard_labels = ""
+encoder = "convnextv2_tiny.fcmae_ft_in22k_in1k"
+out_channels_cls = 8
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.02
+tta = 16
+eval_optim_metric = "mpq"
+n_rounds = 5
+save = false
+f1_metric_ccrop = 248
+match_euc_dist = 6
+eval_criteria = "lizard|alt"
+max_hole_size = 50
+checkpoint_path = ""
+experiment = "convnextv2_tiny_focal_fulldata_0"
+seed = 42
+fold = 0
+test_as_val = true
+optim_metric = "mpq"
+num_workers = 4
+use_amp = true
+color_scale = 0.2
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

lizard_convnextv2_tiny/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:606f3f99c29d247c3c23ede4ca6751d9d413bf790fbf61f7c92fb6ec8d56d9fa
+size 144433889

pannuke_convnextv2_tiny_1/pannuke_test_param_dict.json

@@ -0,0 +1,44 @@
+{
+  "best_fg_lizard": [
+    0.6,
+    0.6,
+    0.5,
+    0.5,
+    0.5
+  ],
+  "best_seed_lizard": [
+    0.6,
+    0.6,
+    0.6,
+    0.5,
+    0.5
+  ],
+  "best_fg_f1": [
+    0.7000000000000001,
+    0.8,
+    0.4,
+    0.2,
+    0.7000000000000001
+  ],
+  "best_seed_f1": [
+    0.5,
+    0.6,
+    0.5,
+    0.4,
+    0.6
+  ],
+  "best_fg_pannuke": [
+    0.6,
+    0.6,
+    0.4,
+    0.5,
+    0.5
+  ],
+  "best_seed_pannuke": [
+    0.6,
+    0.6,
+    0.5,
+    0.5,
+    0.5
+  ]
+}

pannuke_convnextv2_tiny_1/params.toml

@@ -0,0 +1,65 @@
+dataset = "pannuke"
+data_path = ""
+encoder = "convnextv2_tiny.fcmae_ft_in22k_in1k"
+out_channels_cls = 6
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.1
+tta = 16
+eval_optim_metric = "pannuke"
+n_rounds = 5
+save = false
+alt_metric_ccrop = 256
+match_euc_dist = 12
+eval_criteria = "lizard|alt|pannuke"
+max_hole_size = 128
+checkpoint_path = ""
+experiment = "pannuke_convnextv2_tiny_1"
+seed = 42
+fold = 1
+test_as_val = false
+optim_metric = "pannuke"
+num_workers = 4
+use_amp = true
+color_scale = 0.4
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.5
+max = 1.5
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

pannuke_convnextv2_tiny_1/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c75821cfc2a0a49f7f75ebb57a4e4842f9ddd67798841180a6e3d8091261ed0
+size 144433761

pannuke_convnextv2_tiny_2/pannuke_test_param_dict.json

@@ -0,0 +1,44 @@
+{
+  "best_fg_lizard": [
+    0.5,
+    0.6,
+    0.5,
+    0.5,
+    0.6
+  ],
+  "best_seed_lizard": [
+    0.5,
+    0.6,
+    0.6,
+    0.4,
+    0.6
+  ],
+  "best_fg_f1": [
+    0.7000000000000001,
+    0.7000000000000001,
+    0.6,
+    0.30000000000000004,
+    0.7000000000000001
+  ],
+  "best_seed_f1": [
+    0.5,
+    0.4,
+    0.5,
+    0.2,
+    0.6
+  ],
+  "best_fg_pannuke": [
+    0.5,
+    0.6,
+    0.5,
+    0.5,
+    0.5
+  ],
+  "best_seed_pannuke": [
+    0.6,
+    0.6,
+    0.6,
+    0.4,
+    0.5
+  ]
+}

pannuke_convnextv2_tiny_2/params.toml

@@ -0,0 +1,65 @@
+dataset = "pannuke"
+data_path = ""
+encoder = "convnextv2_tiny.fcmae_ft_in22k_in1k"
+out_channels_cls = 6
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.1
+tta = 16
+eval_optim_metric = "pannuke"
+n_rounds = 5
+save = false
+alt_metric_ccrop = 256
+match_euc_dist = 12
+eval_criteria = "lizard|alt|pannuke"
+max_hole_size = 128
+checkpoint_path = ""
+experiment = "pannuke_convnextv2_tiny_2"
+seed = 42
+fold = 2
+test_as_val = false
+optim_metric = "pannuke"
+num_workers = 4
+use_amp = true
+color_scale = 0.4
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.5
+max = 1.5
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

pannuke_convnextv2_tiny_2/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:10d0580bb0616b081d19da90f87196a4db8554963720bf2fe11822d4b215557e
+size 144433761

pannuke_convnextv2_tiny_3/pannuke_test_param_dict.json

@@ -0,0 +1,44 @@
+{
+  "best_fg_lizard": [
+    0.5,
+    0.6,
+    0.5,
+    0.5,
+    0.5
+  ],
+  "best_seed_lizard": [
+    0.5,
+    0.6,
+    0.5,
+    0.4,
+    0.5
+  ],
+  "best_fg_f1": [
+    0.7000000000000001,
+    0.7000000000000001,
+    0.6,
+    0.6,
+    0.7000000000000001
+  ],
+  "best_seed_f1": [
+    0.4,
+    0.5,
+    0.4,
+    0.1,
+    0.5
+  ],
+  "best_fg_pannuke": [
+    0.6,
+    0.6,
+    0.5,
+    0.7000000000000001,
+    0.5
+  ],
+  "best_seed_pannuke": [
+    0.5,
+    0.5,
+    0.5,
+    0.6,
+    0.5
+  ]
+}

pannuke_convnextv2_tiny_3/params.toml

@@ -0,0 +1,65 @@
+dataset = "pannuke"
+data_path = ""
+encoder = "convnextv2_tiny.fcmae_ft_in22k_in1k"
+out_channels_cls = 6
+inst_channels = 5
+pretrained = true
+batch_size = 24
+validation_batch_size = 64
+weight_decay = 0.0001
+learning_rate = 0.0001
+min_learning_rate = 1e-8
+training_steps = 200000
+validation_step = 1000
+checkpoint_step = 10000
+fl_gamma = 2
+loss_lambda = 0.1
+tta = 16
+eval_optim_metric = "pannuke"
+n_rounds = 5
+save = false
+alt_metric_ccrop = 256
+match_euc_dist = 12
+eval_criteria = "lizard|alt|pannuke"
+max_hole_size = 128
+checkpoint_path = ""
+experiment = "pannuke_convnextv2_tiny_3"
+seed = 42
+fold = 3
+test_as_val = false
+optim_metric = "pannuke"
+num_workers = 4
+use_amp = true
+color_scale = 0.4
+
+[aug_params_fast.mirror]
+prob_x = 0.5
+prob_y = 0.5
+prob = 0.5
+
+[aug_params_fast.translate]
+max_percent = 0.05
+prob = 0.2
+
+[aug_params_fast.scale]
+min = 0.8
+max = 1.2
+prob = 0.2
+
+[aug_params_fast.zoom]
+min = 0.5
+max = 1.5
+prob = 0.2
+
+[aug_params_fast.rotate]
+max_degree = 179
+prob = 0.75
+
+[aug_params_fast.shear]
+max_percent = 0.1
+prob = 0.2
+
+[aug_params_fast.elastic]
+alpha = [ 120, 120,]
+sigma = 8
+prob = 0.5

pannuke_convnextv2_tiny_3/train/best_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:12ece143178a4b8fda71014126aab5696d4ba6efbf42f480f56a44ebb54e26f8
+size 144433761