metadata
license: other
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: mobilenet_v2_1.0_224-plant-disease-identification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7145092460881934
mobilenet_v2_1.0_224-plant-disease-identification
This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3799
- Accuracy: 0.7145
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.3889 | 1.0 | 248 | 2.1952 | 0.6310 |
1.8202 | 2.0 | 496 | 1.6363 | 0.7013 |
1.6266 | 3.0 | 744 | 1.6291 | 0.6343 |
1.5566 | 4.0 | 992 | 1.3514 | 0.7129 |
1.5507 | 5.0 | 1240 | 1.3799 | 0.7145 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2