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---
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
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