---
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