---
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-lage-beans-demo-v5
  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. -->

# vit-lage-beans-demo-v5

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1027
- Accuracy: 0.9792

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7861        | 0.28  | 100  | 0.7609          | 0.725    |
| 0.6276        | 0.56  | 200  | 0.6835          | 0.7764   |
| 0.6089        | 0.83  | 300  | 0.5568          | 0.7931   |
| 0.302         | 1.11  | 400  | 0.5887          | 0.8194   |
| 0.1723        | 1.39  | 500  | 0.2988          | 0.8903   |
| 0.2522        | 1.67  | 600  | 0.2564          | 0.9167   |
| 0.1115        | 1.94  | 700  | 0.1680          | 0.9472   |
| 0.1445        | 2.22  | 800  | 0.2065          | 0.9403   |
| 0.0648        | 2.5   | 900  | 0.1673          | 0.9569   |
| 0.0209        | 2.78  | 1000 | 0.1636          | 0.9569   |
| 0.0003        | 3.06  | 1100 | 0.1293          | 0.9694   |
| 0.0034        | 3.33  | 1200 | 0.0817          | 0.9792   |
| 0.0006        | 3.61  | 1300 | 0.0874          | 0.9833   |
| 0.0023        | 3.89  | 1400 | 0.1076          | 0.9778   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0