fixes

model.py

@@ -1,36 +0,0 @@
-import torch
-import torchvision
-
-from torch import nn
-
-
-def create_effnetb2_model(num_classes:int=7, 
-                          seed:int=42):
-    """Creates an EfficientNetB2 feature extractor model and transforms.
-
-    Args:
-        num_classes (int, optional): number of classes in the classifier head. 
-            Defaults to 3.
-        seed (int, optional): random seed value. Defaults to 42.
-
-    Returns:
-        model (torch.nn.Module): EffNetB2 feature extractor model. 
-        transforms (torchvision.transforms): EffNetB2 image transforms.
-    """
-    # Create EffNetB2 pretrained weights, transforms and model
-    weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
-    transforms = weights.transforms()
-    model = torchvision.models.efficientnet_b2(weights=weights)
-
-    # Freeze all layers in base model
-    for param in model.parameters():
-        param.requires_grad = False
-
-    # Change classifier head with random seed for reproducibility
-    torch.manual_seed(seed)
-    model.classifier = nn.Sequential(
-        nn.Dropout(p=0.3, inplace=True),
-        nn.Linear(in_features=1408, out_features=num_classes),
-    )
-    
-    return model, transforms

trained_model.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:421c6b68295a899f6bac78515a32ef97b7f0bfc37bd6ed471944c159abcaaf21
-size 31375357
+oid sha256:1831137969b5dc095fb67ffbd36fb4504d6a2dd2a162aca5fc3913acd6c80e64
+size 31291837