metadata

license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - generated_from_trainer
datasets:
  - beans
metrics:
  - accuracy
model-index:
  - name: plant_disease_detection-beans
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: beans
          type: beans
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9849624060150376

plant_disease_detection-beans

This model is a fine-tuned version of google/vit-base-patch16-224 on the beans dataset. It achieves the following results on the evaluation set:

Loss: 0.0711
Accuracy: 0.9850

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.2
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0983	0.98	16	0.8079	0.7143
0.5524	1.97	32	0.2697	0.9624
0.2699	2.95	48	0.0926	0.9549
0.0991	4.0	65	0.0551	0.9774
0.0722	4.98	81	0.0435	0.9925
0.0584	5.97	97	0.0328	0.9850
0.0451	6.95	113	0.0478	0.9774
0.0321	8.0	130	0.0532	0.9925
0.0298	8.98	146	0.0802	0.9774
0.0516	9.97	162	0.0391	0.9774
0.0396	10.95	178	0.0720	0.9774
0.0358	12.0	195	0.0540	0.9850
0.027	12.98	211	0.0467	0.9774
0.0236	13.97	227	0.0184	0.9925
0.0272	14.95	243	0.0255	0.9925
0.0182	16.0	260	0.0354	0.9850
0.0504	16.98	276	0.0039	1.0
0.0283	17.97	292	0.0199	1.0
0.0241	18.95	308	0.0250	0.9925
0.0268	19.69	320	0.0711	0.9850

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.15.0