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---
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-driverbox
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9879688605803255
---
<!-- 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. -->
# convnext-tiny-224-driverbox
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0497
- Accuracy: 0.9880
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3349 | 0.9950 | 99 | 0.2700 | 0.9328 |
| 0.2393 | 2.0 | 199 | 0.1932 | 0.9540 |
| 0.1831 | 2.9950 | 298 | 0.1403 | 0.9618 |
| 0.1397 | 4.0 | 398 | 0.1055 | 0.9689 |
| 0.0795 | 4.9950 | 497 | 0.1030 | 0.9731 |
| 0.0915 | 6.0 | 597 | 0.0966 | 0.9703 |
| 0.0718 | 6.9950 | 696 | 0.0779 | 0.9745 |
| 0.0502 | 8.0 | 796 | 0.0729 | 0.9788 |
| 0.0314 | 8.9950 | 895 | 0.0621 | 0.9802 |
| 0.0408 | 10.0 | 995 | 0.0758 | 0.9752 |
| 0.0335 | 10.9950 | 1094 | 0.0598 | 0.9823 |
| 0.0228 | 12.0 | 1194 | 0.0573 | 0.9823 |
| 0.0229 | 12.9950 | 1293 | 0.0473 | 0.9844 |
| 0.0119 | 14.0 | 1393 | 0.0642 | 0.9844 |
| 0.028 | 14.9950 | 1492 | 0.0526 | 0.9851 |
| 0.0117 | 16.0 | 1592 | 0.0594 | 0.9837 |
| 0.0187 | 16.9950 | 1691 | 0.0497 | 0.9880 |
| 0.0131 | 18.0 | 1791 | 0.0663 | 0.9837 |
| 0.0132 | 18.9950 | 1890 | 0.0478 | 0.9866 |
| 0.014 | 20.0 | 1990 | 0.0465 | 0.9880 |
| 0.0039 | 20.9950 | 2089 | 0.0496 | 0.9851 |
| 0.0102 | 22.0 | 2189 | 0.0468 | 0.9880 |
| 0.0035 | 22.9950 | 2288 | 0.0581 | 0.9866 |
| 0.0071 | 24.0 | 2388 | 0.0519 | 0.9866 |
| 0.0032 | 24.9950 | 2487 | 0.0510 | 0.9880 |
| 0.0049 | 26.0 | 2587 | 0.0575 | 0.9858 |
| 0.0037 | 26.9950 | 2686 | 0.0511 | 0.9880 |
| 0.0029 | 28.0 | 2786 | 0.0484 | 0.9880 |
| 0.0019 | 28.9950 | 2885 | 0.0523 | 0.9866 |
| 0.0058 | 29.8492 | 2970 | 0.0532 | 0.9866 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
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