hilmansw/resnet18-catdog-classifier

Model description

This model is a fine-tuned version of microsoft/resnet-18 on an custom dataset. This model was built using the "Cats & Dogs Classification" dataset obtained from Kaggle. During the model building process, this was done using the Pytorch framework with pre-trained Resnet-18. The method used during the process of building this classification model is fine-tuning with the dataset.

Training results

Epoch	Accuracy
1.0	0.9357
2.0	0.9786
3.0	0.9000
4.0	0.9214
5.0	0.9143
6.0	0.9429
7.0	0.9714
8.0	0.9929
9.0	0.9714
10.0	0.9714

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• loss_function = CrossEntropyLoss
• optimizer = AdamW
• learning_rate: 0.0001
• batch_size: 16
• num_epochs: 10

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3