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config.json

@@ -6,7 +6,7 @@
     "AutoConfig": "configuration_spice_cnn.SpiceCNNConfig",
     "AutoModelForImageClassification": "modeling_spice_cnn.SpiceCNNModelForImageClassification"
   },
-  "dropout_rate": 0.2,
+  "dropout_rate": 0.4,
   "hidden_size": 128,
   "in_channels": 1,
   "kernel_size": 3,

configuration_spice_cnn.py

@@ -28,7 +28,7 @@ class SpiceCNNConfig(PretrainedConfig):
         self,
         in_channels: int = 3,
         num_classes: int = 10,
-        dropout_rate: float = 0.2,
+        dropout_rate: float = 0.4,
         hidden_size: int = 128,
         num_filters: int = 16,
         kernel_size: int = 3,

modeling_spice_cnn.py

@@ -13,7 +13,7 @@ class SpiceCNNModelForImageClassification(PreTrainedModel):
         layers = [
             nn.Conv2d(
                 config.in_channels,
-                16,
+                32,
                 kernel_size=config.kernel_size,
                 stride=config.stride,
                 padding=config.padding,
@@ -21,8 +21,8 @@ class SpiceCNNModelForImageClassification(PreTrainedModel):
             nn.ReLU(),
             nn.MaxPool2d(kernel_size=config.pooling_size),
             nn.Conv2d(
-                16,
                 32,
+                64,
                 kernel_size=config.kernel_size,
                 stride=config.stride,
                 padding=config.padding,
@@ -30,7 +30,7 @@ class SpiceCNNModelForImageClassification(PreTrainedModel):
             nn.ReLU(),
             nn.MaxPool2d(kernel_size=config.pooling_size),
             nn.Flatten(),
-            nn.Linear(7 * 7 * 32, 128),
+            nn.Linear(7 * 7 * 64, 128),
             nn.ReLU(),
             nn.Linear(128, config.num_classes),
         ]

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b2bd33ae4006b549f8ef4839e107525981d190d4922a7236e5de3a59190450a1
-size 830347
+oid sha256:3e376b1a3eb5151032ae94a61eec980ba20ce42cb3ba4699a3f98de9c106eda7
+size 1689227