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weed_beit_imbalanced

Image Classification
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PyTorch
beit
Generated from Trainer
Eval Results
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weed_beit_imbalanced
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass14
  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: 0.9625
---

<!-- 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_hfclass14
Model is trained on imbalanced dataset/ .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: 0.1414
- Accuracy: 0.9625

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5465        | 1.0   | 69   | 0.3265          | 0.9071   |
| 0.2812        | 2.0   | 138  | 0.2354          | 0.9304   |
| 0.2029        | 3.0   | 207  | 0.1909          | 0.9304   |
| 0.157         | 4.0   | 276  | 0.1910          | 0.9411   |
| 0.1556        | 5.0   | 345  | 0.2176          | 0.9321   |
| 0.1212        | 6.0   | 414  | 0.1597          | 0.9625   |
| 0.1256        | 7.0   | 483  | 0.1335          | 0.9661   |
| 0.0962        | 8.0   | 552  | 0.1714          | 0.9464   |
| 0.1005        | 9.0   | 621  | 0.1453          | 0.9571   |
| 0.0944        | 10.0  | 690  | 0.1414          | 0.9625   |


### Framework versions

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