flower_image_classification_ResNet50_v1.0

flower_image_classification_ResNet50_v1.0

This model is a fine-tuned version of Keras ResNet50 on the tf_flower dataset (https://www.tensorflow.org/datasets/catalog/tf_flowers). It achieves the following results on the evaluation set:

• Loss: 0.7941
• Accuracy: 0.8571

Model description

A slightly customized image classification model for classify 5 labels of flowers ('daisy', 'dandelion', 'roses', 'sunflowers', 'tulips')

Intended uses & limitations

This model is fined tune solely for flower image classification.

Training and evaluation data

Training and testing data is splitted into 80:20 portion. Total data : 3670 files belonging to 5 classes Training data : 2753 files (80%) Validation data : 917 files (20%)

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-03
• train_batch_size: 8
• eval_batch_size: 8
• seed: 1
• optimizer: Adam
• loss: categorical_crossentropy
• num_epochs: 5

Fine-Tuning Results

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0
• opencv-contrib-python-4.10.0.82