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---
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
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