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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_convnext_imbalanced
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: 0.9446428571428571
---
<!-- 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_imbalanced
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 [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: 0.1963
- Accuracy: 0.9446
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0851 | 1.0 | 275 | 0.9525 | 0.8161 |
| 0.3283 | 2.0 | 550 | 0.2921 | 0.925 |
| 0.1298 | 3.0 | 825 | 0.2126 | 0.9411 |
| 0.1583 | 4.0 | 1100 | 0.1959 | 0.9464 |
| 0.1922 | 5.0 | 1375 | 0.2284 | 0.9321 |
| 0.1358 | 6.0 | 1650 | 0.1811 | 0.9607 |
| 0.137 | 7.0 | 1925 | 0.1808 | 0.9446 |
| 0.1524 | 8.0 | 2200 | 0.2534 | 0.9357 |
| 0.0507 | 9.0 | 2475 | 0.1908 | 0.95 |
| 0.1011 | 10.0 | 2750 | 0.1963 | 0.9446 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
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