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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# plant_disease_detection-beans
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/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
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