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mobilenet_v2_1.0_224-plant-disease-identification-ONNX – AI Model by onnx-community | AlphaNeural AI
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mobilenet_v2_1.0_224-plant-disease-identification-ONNX
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transformers.js
onnx
mobilenet_v2
image-classification
generated_from_trainer
image_folder
linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification
quantized
other
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us
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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
