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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

Epoch Step Training Loss Training Accuracy Validation Loss Validation Accuracy
1.0 345 13.9143 0.6478 0.5310 0.8288
2.0 690 0.2639 0.9161 0.6046 0.8419
3.0 1035 0.1369 0.9539 0.5483 0.8561
4.0 1380 0.0863 0.9703 0.5699 0.8659
5.0 1725 0.0686 0.9837 0.7941 0.8571

Framework versions

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