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weed_deit_balanced

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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weed_deit_balanced
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass16
  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: 0.9466666666666667
---

<!-- 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_hfclass16
Model is trained on balanced dataset/250 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 [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1597
- Accuracy: 0.9467

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1694        | 0.99  | 37   | 1.2880          | 0.69     |
| 0.5192        | 1.99  | 74   | 0.3995          | 0.8667   |
| 0.3136        | 2.99  | 111  | 0.3333          | 0.89     |
| 0.2521        | 3.99  | 148  | 0.2672          | 0.91     |
| 0.1693        | 4.99  | 185  | 0.2316          | 0.9167   |
| 0.1747        | 5.99  | 222  | 0.1575          | 0.9567   |
| 0.1324        | 6.99  | 259  | 0.1896          | 0.9467   |
| 0.1102        | 7.99  | 296  | 0.1931          | 0.94     |
| 0.1105        | 8.99  | 333  | 0.1537          | 0.9533   |
| 0.1036        | 9.99  | 370  | 0.1597          | 0.9467   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2