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- ---
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- language:
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- - Python
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- - PyTorch
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- tags:
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- - cifar
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- - cats
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- - upsidedown
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- license: mit
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- datasets:
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- - cifar10_reduced
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- metrics:
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- - Accuracy
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- - Precision
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- - Recall
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- model-index:
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- - name: CatsNet
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- results:
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- - task:
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- type: image-classification
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- name: Image Classification
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- dataset:
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- type: cifar10
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- name: CIFAR10_CATS
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- metrics:
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- - type: Accuracy
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- value: 0.83
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- name: Test Accuracy
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- - type: Precision
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- value: 0.83
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- name: Test Precision
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- - type: Recall
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- value: 0.82
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- name: Test Recall
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- ---
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- Model for Fatima Fellowship code challenge. <br>
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  Full training and evaluation pipelines can be found at: https://colab.research.google.com/drive/1hjHn6EggRDsxOZz5fMo6ZdT-4aKcUCTt
 
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+ ---
2
+ tags:
3
+ - cifar
4
+ - cats
5
+ - upsidedown
6
+ license: mit
7
+ datasets:
8
+ - cifar10_reduced
9
+ metrics:
10
+ - Accuracy
11
+ - Precision
12
+ - Recall
13
+ model-index:
14
+ - name: CatsNet
15
+ results:
16
+ - task:
17
+ type: image-classification
18
+ name: Image Classification
19
+ dataset:
20
+ type: cifar10
21
+ name: CIFAR10_CATS
22
+ metrics:
23
+ - type: Accuracy
24
+ value: 0.83
25
+ name: Test Accuracy
26
+ - type: Precision
27
+ value: 0.83
28
+ name: Test Precision
29
+ - type: Recall
30
+ value: 0.82
31
+ name: Test Recall
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+ ---
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+ Model for Fatima Fellowship code challenge. <br>
 
 
 
34
  Full training and evaluation pipelines can be found at: https://colab.research.google.com/drive/1hjHn6EggRDsxOZz5fMo6ZdT-4aKcUCTt