---
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: 0.954140127388535
---

<!-- 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 [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2858
- Accuracy: 0.9541

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2496        | 1.27  | 500  | 1.2172          | 0.5637   |
| 0.7542        | 2.54  | 1000 | 0.8994          | 0.6898   |
| 0.6158        | 3.82  | 1500 | 0.6794          | 0.7720   |
| 0.4306        | 5.09  | 2000 | 0.4715          | 0.8331   |
| 0.3066        | 6.36  | 2500 | 0.4127          | 0.8567   |
| 0.2851        | 7.63  | 3000 | 0.3460          | 0.8803   |
| 0.3096        | 8.91  | 3500 | 0.2714          | 0.9019   |
| 0.1086        | 10.18 | 4000 | 0.2760          | 0.9268   |
| 0.1209        | 11.45 | 4500 | 0.2881          | 0.9229   |
| 0.1036        | 12.72 | 5000 | 0.2566          | 0.9357   |
| 0.0716        | 13.99 | 5500 | 0.2792          | 0.9382   |
| 0.0168        | 15.27 | 6000 | 0.2604          | 0.9376   |
| 0.0004        | 16.54 | 6500 | 0.3676          | 0.9363   |
| 0.0017        | 17.81 | 7000 | 0.2969          | 0.9529   |
| 0.0005        | 19.08 | 7500 | 0.2858          | 0.9541   |


### Framework versions

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