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_v9.3

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 0.33 100 0.1309 0.7921 0.7604 0.7759 0.9671
No log 0.65 200 0.0526 0.8782 0.8921 0.8851 0.9850
No log 0.98 300 0.0401 0.9011 0.9231 0.9120 0.9887
No log 1.3 400 0.0349 0.9080 0.9386 0.9231 0.9905
0.1604 1.63 500 0.0304 0.9081 0.9438 0.9256 0.9908
0.1604 1.95 600 0.0247 0.9368 0.9559 0.9463 0.9935
0.1604 2.28 700 0.0229 0.9444 0.9593 0.9518 0.9942
0.1604 2.61 800 0.0231 0.9324 0.9604 0.9462 0.9935
0.1604 2.93 900 0.0251 0.9330 0.9645 0.9485 0.9939
0.0267 3.26 1000 0.0234 0.9485 0.9659 0.9571 0.9950
0.0267 3.58 1100 0.0219 0.9463 0.9662 0.9562 0.9948
0.0267 3.91 1200 0.0256 0.9309 0.9662 0.9482 0.9939
0.0267 4.23 1300 0.0209 0.9533 0.9721 0.9626 0.9956
0.0267 4.56 1400 0.0221 0.9484 0.9638 0.9561 0.9948
0.0164 4.89 1500 0.0179 0.9591 0.9690 0.9640 0.9957
0.0164 5.21 1600 0.0187 0.9498 0.9717 0.9606 0.9954
0.0164 5.54 1700 0.0215 0.9516 0.9697 0.9606 0.9952
0.0164 5.86 1800 0.0213 0.9543 0.9707 0.9624 0.9956
0.0164 6.19 1900 0.0212 0.9530 0.9710 0.9619 0.9955
0.0106 6.51 2000 0.0237 0.9466 0.9721 0.9592 0.9953
0.0106 6.84 2100 0.0222 0.9511 0.9724 0.9616 0.9956
0.0106 7.17 2200 0.0221 0.9481 0.9704 0.9591 0.9952
0.0106 7.49 2300 0.0198 0.9463 0.9714 0.9587 0.9952
0.0106 7.82 2400 0.0198 0.9528 0.9741 0.9634 0.9957
0.0075 8.14 2500 0.0197 0.9589 0.9741 0.9665 0.9961
0.0075 8.47 2600 0.0204 0.9616 0.9759 0.9687 0.9964
0.0075 8.79 2700 0.0209 0.9538 0.9741 0.9638 0.9958
0.0075 9.12 2800 0.0222 0.9521 0.9721 0.9620 0.9955
0.0075 9.45 2900 0.0195 0.9623 0.9755 0.9688 0.9964
0.0059 9.77 3000 0.0204 0.9550 0.9738 0.9643 0.9959
0.0059 10.1 3100 0.0204 0.9576 0.9735 0.9655 0.9961
0.0059 10.42 3200 0.0201 0.9550 0.9731 0.9640 0.9959
0.0059 10.75 3300 0.0205 0.9547 0.9735 0.9640 0.9959
0.0059 11.07 3400 0.0206 0.9541 0.9741 0.9640 0.9959
0.0041 11.4 3500 0.0203 0.9551 0.9745 0.9647 0.9959

Framework versions