generated_from_trainer

<!-- 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. -->

perioli_manifesti_v9.4

This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 0.31 100 0.1646 0.6916 0.6226 0.6553 0.9487
No log 0.62 200 0.0816 0.8202 0.8779 0.8481 0.9788
No log 0.93 300 0.0412 0.8885 0.9251 0.9064 0.9880
No log 1.25 400 0.0298 0.9273 0.9375 0.9324 0.9918
0.1823 1.56 500 0.0269 0.9388 0.9418 0.9403 0.9925
0.1823 1.87 600 0.0211 0.9563 0.9553 0.9558 0.9942
0.1823 2.18 700 0.0249 0.9287 0.9663 0.9471 0.9936
0.1823 2.49 800 0.0174 0.9547 0.9659 0.9603 0.9952
0.1823 2.8 900 0.0170 0.9564 0.9666 0.9615 0.9955
0.0283 3.12 1000 0.0185 0.9501 0.9663 0.9581 0.9950
0.0283 3.43 1100 0.0170 0.9594 0.9720 0.9656 0.9960
0.0283 3.74 1200 0.0196 0.9462 0.9677 0.9568 0.9949
0.0283 4.05 1300 0.0171 0.9536 0.9702 0.9618 0.9957
0.0283 4.36 1400 0.0169 0.9612 0.9752 0.9681 0.9964
0.0156 4.67 1500 0.0151 0.9646 0.9759 0.9702 0.9967
0.0156 4.98 1600 0.0166 0.9573 0.9720 0.9646 0.9959
0.0156 5.3 1700 0.0160 0.9628 0.9748 0.9688 0.9965
0.0156 5.61 1800 0.0158 0.9588 0.9748 0.9667 0.9963
0.0156 5.92 1900 0.0168 0.9574 0.9737 0.9655 0.9961
0.012 6.23 2000 0.0198 0.9525 0.9748 0.9635 0.9959
0.012 6.54 2100 0.0196 0.9508 0.9737 0.9621 0.9958
0.012 6.85 2200 0.0166 0.9628 0.9744 0.9686 0.9965
0.012 7.17 2300 0.0171 0.9636 0.9773 0.9704 0.9967
0.012 7.48 2400 0.0170 0.9619 0.9769 0.9694 0.9967
0.0087 7.79 2500 0.0179 0.9612 0.9755 0.9683 0.9965
0.0087 8.1 2600 0.0168 0.9649 0.9766 0.9707 0.9967
0.0087 8.41 2700 0.0179 0.9642 0.9766 0.9704 0.9967
0.0087 8.72 2800 0.0179 0.9636 0.9780 0.9708 0.9968
0.0087 9.03 2900 0.0172 0.9626 0.9769 0.9697 0.9967
0.0065 9.35 3000 0.0170 0.9636 0.9773 0.9704 0.9967

Framework versions