---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: plant-seedlings-model-beit
  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: 0.8968565815324165
---

<!-- 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-beit

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3466
- Accuracy: 0.8969

## 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4966        | 0.8   | 100  | 1.2583          | 0.5909   |
| 0.8239        | 1.6   | 200  | 0.9266          | 0.6979   |
| 0.7583        | 2.4   | 300  | 0.6527          | 0.7834   |
| 0.5222        | 3.2   | 400  | 0.5186          | 0.8035   |
| 0.5233        | 4.0   | 500  | 0.5527          | 0.8060   |
| 0.516         | 4.8   | 600  | 0.5558          | 0.8148   |
| 0.4848        | 5.6   | 700  | 0.4780          | 0.8409   |
| 0.1949        | 6.4   | 800  | 0.5876          | 0.8320   |
| 0.2581        | 7.2   | 900  | 0.4364          | 0.8482   |
| 0.2748        | 8.0   | 1000 | 0.3565          | 0.8777   |
| 0.2973        | 8.8   | 1100 | 0.4623          | 0.8615   |
| 0.1655        | 9.6   | 1200 | 0.3700          | 0.8875   |
| 0.1744        | 10.4  | 1300 | 0.3751          | 0.8905   |
| 0.3044        | 11.2  | 1400 | 0.3799          | 0.8919   |
| 0.0981        | 12.0  | 1500 | 0.3466          | 0.8969   |


### Framework versions

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