---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: plant-seedlings-model
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.978343949044586
---

<!-- 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-seedlings-model

This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1235
- Accuracy: 0.9783

## 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3236        | 1.27  | 500  | 0.2747          | 0.9019   |
| 0.2273        | 2.54  | 1000 | 0.3031          | 0.9038   |
| 0.082         | 3.82  | 1500 | 0.2103          | 0.9280   |
| 0.061         | 5.09  | 2000 | 0.2235          | 0.9408   |
| 0.0668        | 6.36  | 2500 | 0.1633          | 0.9554   |
| 0.0739        | 7.63  | 3000 | 0.1561          | 0.9586   |
| 0.0836        | 8.91  | 3500 | 0.1904          | 0.9446   |
| 0.0078        | 10.18 | 4000 | 0.2045          | 0.9535   |
| 0.087         | 11.45 | 4500 | 0.4487          | 0.9146   |
| 0.0119        | 12.72 | 5000 | 0.2162          | 0.9567   |
| 0.0002        | 13.99 | 5500 | 0.1157          | 0.9758   |
| 0.0001        | 15.27 | 6000 | 0.1199          | 0.9771   |
| 0.0001        | 16.54 | 6500 | 0.1215          | 0.9790   |
| 0.0001        | 17.81 | 7000 | 0.1223          | 0.9790   |
| 0.0001        | 19.08 | 7500 | 0.1235          | 0.9783   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3