---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-base-224-22k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: validated_cracks_dataset_relabeled_convnext_model
  results: []
---

<!-- 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. -->

# validated_cracks_dataset_relabeled_convnext_model

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the Logiroad/validated_cracks_dataset_relabeled dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9692
- Accuracy: 0.6332

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 30.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3724        | 1.0   | 108  | 1.3528          | 0.3359   |
| 1.3528        | 2.0   | 216  | 1.2849          | 0.4208   |
| 1.2839        | 3.0   | 324  | 1.2019          | 0.4633   |
| 1.2608        | 4.0   | 432  | 1.1560          | 0.5212   |
| 1.2178        | 5.0   | 540  | 1.0907          | 0.5560   |
| 1.1624        | 6.0   | 648  | 1.0543          | 0.5290   |
| 1.1108        | 7.0   | 756  | 1.0452          | 0.5598   |
| 1.1028        | 8.0   | 864  | 1.0569          | 0.5598   |
| 1.1023        | 9.0   | 972  | 1.0580          | 0.5676   |
| 1.0572        | 10.0  | 1080 | 1.0031          | 0.6139   |
| 0.9874        | 11.0  | 1188 | 1.0340          | 0.5830   |
| 1.0132        | 12.0  | 1296 | 1.0049          | 0.6100   |
| 0.9898        | 13.0  | 1404 | 0.9875          | 0.6216   |
| 1.0182        | 14.0  | 1512 | 0.9668          | 0.6100   |
| 0.9889        | 15.0  | 1620 | 0.9692          | 0.6332   |
| 0.9446        | 16.0  | 1728 | 0.9777          | 0.6332   |
| 0.9519        | 17.0  | 1836 | 1.0030          | 0.5985   |
| 0.9458        | 18.0  | 1944 | 0.9748          | 0.5985   |
| 0.9347        | 19.0  | 2052 | 0.9744          | 0.6178   |
| 0.8863        | 20.0  | 2160 | 0.9657          | 0.6293   |
| 0.8507        | 21.0  | 2268 | 0.9784          | 0.6255   |
| 0.8712        | 22.0  | 2376 | 0.9790          | 0.6255   |
| 0.8857        | 23.0  | 2484 | 0.9682          | 0.6178   |
| 0.8848        | 24.0  | 2592 | 0.9723          | 0.6255   |
| 0.904         | 25.0  | 2700 | 0.9754          | 0.6178   |
| 0.943         | 26.0  | 2808 | 0.9710          | 0.6216   |
| 0.862         | 27.0  | 2916 | 0.9717          | 0.6178   |
| 0.864         | 28.0  | 3024 | 0.9705          | 0.6178   |
| 0.8879        | 29.0  | 3132 | 0.9703          | 0.6178   |
| 0.8099        | 30.0  | 3240 | 0.9703          | 0.6178   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3