---
tags:
- image-classification
- torch
- deep-learning
license: mit
library_name: torch
task_categories:
- image-classification
---

# Cats & Dogs Classifier

This model is a simple neural network trained to classify images of cats and dogs. It is built using PyTorch and trained on the `louiecerv/cats_dogs_dataset` dataset.

## Model Details
- **Architecture**: Fully connected neural network
- **Input Size**: 128x128 RGB images
- **Number of Classes**: 2 (Cats & Dogs)
- **Optimizer**: Adam
- **Loss Function**: CrossEntropyLoss
- **Training Epochs**: 5
- **Dataset**: [Cats & Dogs Dataset](https://huggingface.co/datasets/louiecerv/cats_dogs_dataset)

## Training
The model was trained using a basic fully connected neural network with ReLU activation functions. The training process involved using the Adam optimizer with a learning rate of `0.001`.

## Usage
```python
import torch
from model import ImageClassifier

model = ImageClassifier(input_size=128*128*3, n_classes=2)
model.load_state_dict(torch.load("cats_dogs_classifier.pth"))
model.eval()
```

## License
This model is released under the MIT license.