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---
datasets:
- cats_vs_dogs
metrics:
- accuracy
---
CNN Model for binary classification trained on the cats_vs_dogs dataset from tensorflow datasets. [Training Colab](https://colab.research.google.com/drive/16KYoiNPuNkOxTf3NExqeNQUuOkuL-VJ9?usp=sharing).
The model was trained for 21h53m on a GCE VM instance (n1-standard-4, 1 x NVIDIA T4) and achieved an accuracy of 74.83% on the test split (10% of the dataset).
The model trained for 90 epochs. Last few epochs' metrics:
```
After 28122 steps, test loss: 0.5549, test accuracy: 0.7418
After 28449 steps, test loss: 0.5515, test accuracy: 0.7491
After 28776 steps, test loss: 0.5508, test accuracy: 0.7487
After 29103 steps, test loss: 0.5503, test accuracy: 0.7478
After 29430 steps, test loss: 0.5510, test accuracy: 0.7483
```
| Image | Prediction |
| ----- | ---------- |
|  | Model Prediction - Dog (60.82%), Cat (39.18%) |
|  | Model Prediction - Cat (72.34%), Dog (27.66%) |
|  | Model Prediction - Cat (67.55%), Dog (32.45%) |
|  | Model Prediction - Dog (51.24%), Cat (48.76%) |
|  | Model Prediction - Dog (72.80%), Cat (27.20%) | |