Logiroad
/

Cracks_dataset_2026_convnext_model

+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/convnext-base-224-22k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Cracks_dataset_2026_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. -->
+# Cracks_dataset_2026_convnext_model
+This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8048
+- Accuracy: 0.7177
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3158        | 1.0   | 302  | 1.2774          | 0.4030   |
+| 1.0948        | 2.0   | 604  | 1.0307          | 0.6045   |
+| 1.0577        | 3.0   | 906  | 0.9374          | 0.6480   |
+| 0.9709        | 4.0   | 1208 | 0.8760          | 0.6766   |
+| 0.8839        | 5.0   | 1510 | 0.8935          | 0.6654   |
+| 0.8254        | 6.0   | 1812 | 0.8503          | 0.6990   |
+| 0.9047        | 7.0   | 2114 | 0.8020          | 0.7114   |
+| 0.9098        | 8.0   | 2416 | 0.8173          | 0.7127   |
+| 0.8357        | 9.0   | 2718 | 0.8086          | 0.7002   |
+| 0.8455        | 10.0  | 3020 | 0.8114          | 0.6828   |
+| 0.8015        | 11.0  | 3322 | 0.7899          | 0.7164   |
+| 0.8386        | 12.0  | 3624 | 0.8763          | 0.6803   |
+| 0.7725        | 13.0  | 3926 | 0.7981          | 0.7065   |
+| 0.7663        | 14.0  | 4228 | 0.7917          | 0.7264   |
+| 0.7314        | 15.0  | 4530 | 0.8059          | 0.7127   |
+| 0.7152        | 16.0  | 4832 | 0.8065          | 0.7127   |
+| 0.6853        | 17.0  | 5134 | 0.7929          | 0.7251   |
+| 0.6986        | 18.0  | 5436 | 0.7788          | 0.7413   |
+| 0.6992        | 19.0  | 5738 | 0.7908          | 0.7226   |
+| 0.6889        | 20.0  | 6040 | 0.8038          | 0.7276   |
+| 0.6616        | 21.0  | 6342 | 0.8265          | 0.7114   |
+| 0.6589        | 22.0  | 6644 | 0.8011          | 0.7301   |
+| 0.7379        | 23.0  | 6946 | 0.8198          | 0.7090   |
+| 0.6684        | 24.0  | 7248 | 0.7985          | 0.7264   |
+| 0.6984        | 25.0  | 7550 | 0.7998          | 0.7214   |
+| 0.6881        | 26.0  | 7852 | 0.7948          | 0.7313   |
+| 0.6624        | 27.0  | 8154 | 0.8071          | 0.7102   |
+| 0.6727        | 28.0  | 8456 | 0.8075          | 0.7152   |
+| 0.7003        | 29.0  | 8758 | 0.8049          | 0.7201   |
+| 0.6273        | 30.0  | 9060 | 0.8048          | 0.7177   |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.3.0
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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