metadata
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_raw_dataset_359_convnext_model
results: []
Validated_cracks_raw_dataset_359_convnext_model
This model is a fine-tuned version of facebook/convnext-base-224-22k on the Logiroad/Validated_cracks_raw_dataset_359 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0441
- Accuracy: 0.6021
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 | 1.3690 | 0.3134 |
| 1.3528 | 2.0 | 216 | 1.3015 | 0.4014 |
| 1.2839 | 3.0 | 324 | 1.2375 | 0.4331 |
| 1.2608 | 4.0 | 432 | 1.1975 | 0.4930 |
| 1.2178 | 5.0 | 540 | 1.1368 | 0.5246 |
| 1.1624 | 6.0 | 648 | 1.1164 | 0.4965 |
| 1.1108 | 7.0 | 756 | 1.1063 | 0.5282 |
| 1.1028 | 8.0 | 864 | 1.1174 | 0.5317 |
| 1.1023 | 9.0 | 972 | 1.1123 | 0.5458 |
| 1.0572 | 10.0 | 1080 | 1.0755 | 0.5739 |
| 0.9874 | 11.0 | 1188 | 1.0952 | 0.5599 |
| 1.0132 | 12.0 | 1296 | 1.0767 | 0.5775 |
| 0.9898 | 13.0 | 1404 | 1.0616 | 0.5880 |
| 1.0182 | 14.0 | 1512 | 1.0420 | 0.5810 |
| 0.9889 | 15.0 | 1620 | 1.0441 | 0.6021 |
| 0.9446 | 16.0 | 1728 | 1.0512 | 0.6021 |
| 0.9519 | 17.0 | 1836 | 1.0737 | 0.5704 |
| 0.9458 | 18.0 | 1944 | 1.0471 | 0.5669 |
| 0.9347 | 19.0 | 2052 | 1.0513 | 0.5845 |
| 0.8863 | 20.0 | 2160 | 1.0428 | 0.5951 |
| 0.8507 | 21.0 | 2268 | 1.0527 | 0.5951 |
| 0.8712 | 22.0 | 2376 | 1.0560 | 0.5915 |
| 0.8857 | 23.0 | 2484 | 1.0447 | 0.5880 |
| 0.8848 | 24.0 | 2592 | 1.0512 | 0.5951 |
| 0.904 | 25.0 | 2700 | 1.0513 | 0.5845 |
| 0.943 | 26.0 | 2808 | 1.0480 | 0.5880 |
| 0.862 | 27.0 | 2916 | 1.0476 | 0.5880 |
| 0.864 | 28.0 | 3024 | 1.0469 | 0.5880 |
| 0.8879 | 29.0 | 3132 | 1.0468 | 0.5880 |
| 0.8099 | 30.0 | 3240 | 1.0468 | 0.5880 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3