---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Crop_Disease_model
  results: []
---

<!-- 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. -->

# Crop_Disease_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4412
- Accuracy: 0.6533

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.9809        | 0.9787  | 23   | 2.9338          | 0.144    |
| 2.7916        | 2.0     | 47   | 2.6349          | 0.4693   |
| 2.3529        | 2.9787  | 70   | 2.3237          | 0.4973   |
| 2.0897        | 4.0     | 94   | 2.0598          | 0.532    |
| 1.8713        | 4.9787  | 117  | 1.8989          | 0.5453   |
| 1.6276        | 6.0     | 141  | 1.7701          | 0.584    |
| 1.5641        | 6.9787  | 164  | 1.6756          | 0.612    |
| 1.4144        | 8.0     | 188  | 1.6190          | 0.62     |
| 1.3294        | 8.9787  | 211  | 1.5457          | 0.6373   |
| 1.2586        | 10.0    | 235  | 1.4913          | 0.644    |
| 1.2052        | 10.9787 | 258  | 1.4816          | 0.6227   |
| 1.1644        | 12.0    | 282  | 1.4547          | 0.6387   |
| 1.1158        | 12.9787 | 305  | 1.4392          | 0.6453   |
| 1.0931        | 14.0    | 329  | 1.4277          | 0.6507   |
| 1.0969        | 14.6809 | 345  | 1.4412          | 0.6533   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1