mobilenet_v2_1.0_224-plant-disease-identification (ONNX)

This is an ONNX version of linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification. It was automatically converted and uploaded using this Hugging Face Space.

Usage with Transformers.js

See the pipeline documentation for image-classification: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.ImageClassificationPipeline


mobilenet_v2_1.0_224-plant-disease-identification

This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the Kaggle version of the Plant Village dataset. It achieves the following results on the evaluation set:

  • Cross Entropy Loss: 0.15
  • Accuracy: 0.9541

Intended uses & limitations

For identifying common diseases in crops and assessing plant health. Not to be used as a replacement for an actual diagnosis from experts.

Training and evaluation data

The plant village dataset consists of 38 classes of diseases in common crops (including healthy/normal crops).

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-5
  • train_batch_size: 256
  • eval_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.2
  • num_epochs: 6

Framework versions

  • Transformers 4.27.3
  • Pytorch 1.13.0
  • Datasets 2.1.0
  • Tokenizers 0.13.2
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Evaluation results