Training in progress, step 100

config.json

@@ -1,7 +1,7 @@
 {
-  "_name_or_path": "microsoft/swin-tiny-patch4-window7-224",
+  "_name_or_path": "microsoft/swinv2-tiny-patch4-window8-256",
   "architectures": [
-    "SwinForImageClassification"
+    "Swinv2ForImageClassification"
   ],
   "attention_probs_dropout_prob": 0.0,
   "depths": [
@@ -22,7 +22,7 @@
     "2": "Invasive",
     "3": "Normal"
   },
-  "image_size": 224,
+  "image_size": 256,
   "initializer_range": 0.02,
   "label2id": {
     "Benign": "0",
@@ -32,7 +32,7 @@
   },
   "layer_norm_eps": 1e-05,
   "mlp_ratio": 4.0,
-  "model_type": "swin",
+  "model_type": "swinv2",
   "num_channels": 3,
   "num_heads": [
     3,
@@ -41,20 +41,18 @@
     24
   ],
   "num_layers": 4,
-  "out_features": null,
   "patch_size": 4,
   "path_norm": true,
+  "pretrained_window_sizes": [
+    0,
+    0,
+    0,
+    0
+  ],
   "problem_type": "single_label_classification",
   "qkv_bias": true,
-  "stage_names": [
-    "stem",
-    "stage1",
-    "stage2",
-    "stage3",
-    "stage4"
-  ],
   "torch_dtype": "float32",
-  "transformers_version": "4.26.1",
+  "transformers_version": "4.27.3",
   "use_absolute_embeddings": false,
-  "window_size": 7
+  "window_size": 8
 }

preprocessor_config.json

@@ -16,7 +16,7 @@
   "resample": 3,
   "rescale_factor": 0.00392156862745098,
   "size": {
-    "height": 224,
-    "width": 224
+    "height": 256,
+    "width": 256
   }
 }

pytorch_model.bin

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training_args.bin

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