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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-base-224-22k |
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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_boost9 |
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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_boost9 |
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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_Balanced_Raw_Dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2586 |
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- Accuracy: 0.4151 |
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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: 8 |
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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: 25.0 |
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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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| 1.3942 | 1.0 | 80 | 1.3566 | 0.3349 | |
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| 1.3192 | 2.0 | 160 | 1.3104 | 0.3585 | |
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| 1.2795 | 3.0 | 240 | 1.2999 | 0.3726 | |
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| 1.2419 | 4.0 | 320 | 1.2860 | 0.3726 | |
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| 1.2213 | 5.0 | 400 | 1.2894 | 0.3679 | |
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| 1.2287 | 6.0 | 480 | 1.2863 | 0.3632 | |
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| 1.2123 | 7.0 | 560 | 1.2879 | 0.3915 | |
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| 1.2124 | 8.0 | 640 | 1.2767 | 0.3868 | |
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| 1.2144 | 9.0 | 720 | 1.2851 | 0.3726 | |
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| 1.2202 | 10.0 | 800 | 1.2683 | 0.3962 | |
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| 1.1804 | 11.0 | 880 | 1.2659 | 0.4009 | |
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| 1.2031 | 12.0 | 960 | 1.2658 | 0.3962 | |
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| 1.1428 | 13.0 | 1040 | 1.2621 | 0.4057 | |
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| 1.1224 | 14.0 | 1120 | 1.2655 | 0.4104 | |
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| 1.1486 | 15.0 | 1200 | 1.2606 | 0.3962 | |
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| 1.1451 | 16.0 | 1280 | 1.2636 | 0.4057 | |
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| 1.1717 | 17.0 | 1360 | 1.2596 | 0.4057 | |
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| 1.1231 | 18.0 | 1440 | 1.2626 | 0.4057 | |
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| 1.1468 | 19.0 | 1520 | 1.2617 | 0.3962 | |
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| 1.0958 | 20.0 | 1600 | 1.2586 | 0.4151 | |
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| 1.1456 | 21.0 | 1680 | 1.2587 | 0.4104 | |
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| 1.127 | 22.0 | 1760 | 1.2590 | 0.4151 | |
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| 1.1308 | 23.0 | 1840 | 1.2586 | 0.4151 | |
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| 1.1433 | 24.0 | 1920 | 1.2585 | 0.4151 | |
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| 1.1492 | 25.0 | 2000 | 1.2585 | 0.4151 | |
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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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