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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass12
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.96
---
<!-- 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. -->
# weeds_hfclass12
Model is trained on balanced dataset/ 250 image per class/ .8 .1 .1 split/ 224x224 resized
Dataset: https://www.kaggle.com/datasets/vbookshelf/v2-plant-seedlings-dataset
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: 0.1257
- Accuracy: 0.96
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6013 | 0.99 | 37 | 0.7579 | 0.8067 |
| 0.3887 | 1.99 | 74 | 0.2834 | 0.9033 |
| 0.2846 | 2.99 | 111 | 0.2767 | 0.9 |
| 0.2086 | 3.99 | 148 | 0.2642 | 0.9067 |
| 0.1664 | 4.99 | 185 | 0.2016 | 0.9333 |
| 0.168 | 5.99 | 222 | 0.1498 | 0.9533 |
| 0.1159 | 6.99 | 259 | 0.1607 | 0.9533 |
| 0.1195 | 7.99 | 296 | 0.1719 | 0.9467 |
| 0.1013 | 8.99 | 333 | 0.1442 | 0.9533 |
| 0.0939 | 9.99 | 370 | 0.1257 | 0.96 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
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