---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_convnext_balanced
  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: 0.9333333333333333
---

<!-- 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_convnext_balanced

This model is a fine-tuned version of [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1931
- Accuracy: 0.9333

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0584        | 1.0   | 150  | 1.9386          | 0.6      |
| 0.7729        | 2.0   | 300  | 0.6873          | 0.8733   |
| 0.4394        | 3.0   | 450  | 0.4321          | 0.89     |
| 0.3337        | 4.0   | 600  | 0.3227          | 0.9      |
| 0.2489        | 5.0   | 750  | 0.2320          | 0.9267   |
| 0.1998        | 6.0   | 900  | 0.2556          | 0.9233   |
| 0.1994        | 7.0   | 1050 | 0.2538          | 0.92     |
| 0.1573        | 8.0   | 1200 | 0.2224          | 0.9333   |
| 0.143         | 9.0   | 1350 | 0.1495          | 0.96     |
| 0.0686        | 10.0  | 1500 | 0.1931          | 0.9333   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.11.0