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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/convnext-small-224 |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Validated_Balanced_Raw_Data_model_boost8 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Validated_Balanced_Raw_Data_model_boost8 |
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This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the Logiroad/Validated_Balanced_Raw_Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1054 |
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- Accuracy: 0.5425 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 1337 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 25 |
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- mixed_precision_training: Native AMP |
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- label_smoothing_factor: 0.05 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.326 | 1.0 | 80 | 1.2990 | 0.3868 | |
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| 1.2698 | 2.0 | 160 | 1.2875 | 0.3726 | |
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| 1.2271 | 3.0 | 240 | 1.2136 | 0.4245 | |
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| 1.1742 | 4.0 | 320 | 1.1844 | 0.4717 | |
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| 1.1507 | 5.0 | 400 | 1.1472 | 0.4906 | |
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| 1.1228 | 6.0 | 480 | 1.1568 | 0.4623 | |
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| 1.0484 | 7.0 | 560 | 1.1222 | 0.4811 | |
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| 1.0224 | 8.0 | 640 | 1.1054 | 0.5425 | |
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| 0.9876 | 9.0 | 720 | 1.1333 | 0.5 | |
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| 0.9897 | 10.0 | 800 | 1.1368 | 0.4811 | |
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| 0.9133 | 11.0 | 880 | 1.0923 | 0.5 | |
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| 0.8814 | 12.0 | 960 | 1.1101 | 0.4717 | |
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| 0.8185 | 13.0 | 1040 | 1.1416 | 0.4953 | |
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| 0.7917 | 14.0 | 1120 | 1.1237 | 0.5047 | |
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| 0.7773 | 15.0 | 1200 | 1.0994 | 0.5047 | |
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| 0.7289 | 16.0 | 1280 | 1.1059 | 0.5094 | |
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| 0.7337 | 17.0 | 1360 | 1.1085 | 0.5142 | |
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| 0.7052 | 18.0 | 1440 | 1.1131 | 0.5189 | |
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| 0.6703 | 19.0 | 1520 | 1.1068 | 0.5330 | |
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| 0.6482 | 20.0 | 1600 | 1.1251 | 0.5189 | |
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| 0.6421 | 21.0 | 1680 | 1.1164 | 0.5283 | |
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| 0.6738 | 22.0 | 1760 | 1.1147 | 0.5377 | |
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| 0.6459 | 23.0 | 1840 | 1.1152 | 0.5283 | |
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| 0.6302 | 24.0 | 1920 | 1.1156 | 0.5283 | |
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| 0.689 | 25.0 | 2000 | 1.1157 | 0.5283 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.3.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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