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README.md

@@ -1,37 +1,36 @@
----
-language: 
-- Python
-- PyTorch
-tags:
-- cifar
-- cats
-- upsidedown
-license: mit
-datasets:
-- cifar10_reduced
-metrics:
-- Accuracy
-- Precision
-- Recall
-model-index:
-- name: CatsNet
-  results:
-  - task: 
-      type: image-classification  
-      name: Image Classification  
-    dataset:
-      type: cifar10  
-      name: CIFAR10_CATS
-    metrics:
-      - type: Accuracy 
-        value: 0.83     
-        name: Test Accuracy    
-      - type: Precision 
-        value: 0.83    
-        name: Test Precision 
-      - type: Recall 
-        value: 0.82     
-        name: Test Recall 
----
-Model for Fatima Fellowship code challenge. <br>
+---
+language: code
+license: mit
+tags:
+- cifar
+- cats
+- upsidedown
+datasets:
+- cifar10_reduced
+metrics:
+- Accuracy
+- Precision
+- Recall
+model-index:
+- name: CatsNet
+  results:
+  - task:
+      type: image-classification
+      name: Image Classification
+    dataset:
+      name: CIFAR10_CATS
+      type: cifar10
+    metrics:
+    - type: Accuracy
+      value: 0.83
+      name: Test Accuracy
+    - type: Precision
+      value: 0.83
+      name: Test Precision
+    - type: Recall
+      value: 0.82
+      name: Test Recall
+---
+
+Model for Fatima Fellowship code challenge. <br>
 Full training and evaluation pipelines can be found at: https://colab.research.google.com/drive/1hjHn6EggRDsxOZz5fMo6ZdT-4aKcUCTt