Document Classification
Collection
4 items
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Updated
This model is a fine-tuned version of microsoft/dit-base.
It achieves the following results on the evaluation set:
For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Document%20AI/Multiclass%20Classification/Document%20Classification%20-%20Desafio%201/Document%20Classification%20-%20Desafio%201.ipynb
This model is intended to demonstrate my ability to solve a complex problem using technology.
Dataset Source: https://www.kaggle.com/datasets/rywgar/document-classification-desafio-1
The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.8316 | 0.99 | 62 | 0.7519 | 0.743 | 0.7020 | 0.743 | 0.7015 | 0.743 | 0.743 | 0.7430 | 0.6827 | 0.743 | 0.6819 |
0.3561 | 2.0 | 125 | 0.2302 | 0.9395 | 0.9401 | 0.9395 | 0.9400 | 0.9395 | 0.9395 | 0.9394 | 0.9482 | 0.9395 | 0.9480 |
0.2222 | 2.99 | 187 | 0.1350 | 0.956 | 0.9564 | 0.956 | 0.9561 | 0.956 | 0.956 | 0.9551 | 0.9598 | 0.956 | 0.9600 |
0.1705 | 4.0 | 250 | 0.0873 | 0.9725 | 0.9727 | 0.9725 | 0.9725 | 0.9725 | 0.9725 | 0.9721 | 0.9740 | 0.9725 | 0.9740 |
0.1541 | 4.99 | 312 | 0.0642 | 0.9825 | 0.9825 | 0.9825 | 0.9824 | 0.9825 | 0.9825 | 0.9822 | 0.9830 | 0.9825 | 0.9830 |
0.1253 | 6.0 | 375 | 0.0330 | 0.9915 | 0.9915 | 0.9915 | 0.9914 | 0.9915 | 0.9915 | 0.9913 | 0.9916 | 0.9915 | 0.9916 |
0.1196 | 6.99 | 437 | 0.0524 | 0.982 | 0.9822 | 0.982 | 0.9820 | 0.982 | 0.982 | 0.9817 | 0.9832 | 0.982 | 0.9832 |
0.0896 | 7.94 | 496 | 0.0436 | 0.9865 | 0.9865 | 0.9865 | 0.9863 | 0.9865 | 0.9865 | 0.9861 | 0.9869 | 0.9865 | 0.9870 |