generated_from_trainer

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perioli_manifesti_v8.3

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 0.37 100 0.1334 0.7328 0.7546 0.7435 0.9605
No log 0.74 200 0.0562 0.8838 0.9128 0.8981 0.9862
No log 1.11 300 0.0520 0.8679 0.9311 0.8984 0.9858
No log 1.48 400 0.0392 0.8995 0.9345 0.9167 0.9888
0.149 1.85 500 0.0306 0.9235 0.9535 0.9383 0.9921
0.149 2.22 600 0.0263 0.9399 0.9542 0.9470 0.9933
0.149 2.59 700 0.0253 0.9404 0.9576 0.9489 0.9935
0.149 2.96 800 0.0243 0.9407 0.9576 0.9491 0.9935
0.149 3.33 900 0.0276 0.9225 0.9607 0.9412 0.9927
0.0267 3.7 1000 0.0252 0.9329 0.9638 0.9481 0.9936
0.0267 4.07 1100 0.0186 0.9517 0.9704 0.9609 0.9953
0.0267 4.44 1200 0.0218 0.9506 0.9624 0.9565 0.9946
0.0267 4.81 1300 0.0188 0.9567 0.9666 0.9616 0.9954
0.0267 5.19 1400 0.0195 0.9573 0.9728 0.9650 0.9957
0.0153 5.56 1500 0.0238 0.9526 0.9628 0.9577 0.9946
0.0153 5.93 1600 0.0211 0.9469 0.9704 0.9585 0.9950
0.0153 6.3 1700 0.0218 0.9474 0.9679 0.9575 0.9949
0.0153 6.67 1800 0.0218 0.9478 0.9700 0.9588 0.9951
0.0153 7.04 1900 0.0204 0.9559 0.9707 0.9632 0.9955
0.01 7.41 2000 0.0211 0.9498 0.9728 0.9612 0.9954
0.01 7.78 2100 0.0198 0.9589 0.9741 0.9665 0.9960
0.01 8.15 2200 0.0187 0.9609 0.9738 0.9673 0.9961
0.01 8.52 2300 0.0193 0.9606 0.9759 0.9682 0.9963
0.01 8.89 2400 0.0212 0.9540 0.9717 0.9628 0.9956
0.0071 9.26 2500 0.0203 0.9579 0.9728 0.9653 0.9959
0.0071 9.63 2600 0.0200 0.9590 0.9752 0.9670 0.9960
0.0071 10.0 2700 0.0215 0.9515 0.9735 0.9623 0.9955
0.0071 10.37 2800 0.0209 0.9586 0.9748 0.9667 0.9960
0.0071 10.74 2900 0.0191 0.9589 0.9741 0.9665 0.9961
0.0051 11.11 3000 0.0194 0.9606 0.9738 0.9671 0.9961
0.0051 11.48 3100 0.0209 0.9561 0.9755 0.9657 0.9961
0.0051 11.85 3200 0.0202 0.9580 0.9741 0.9660 0.9961
0.0051 12.22 3300 0.0210 0.9589 0.9738 0.9663 0.9961
0.0051 12.59 3400 0.0200 0.9583 0.9745 0.9663 0.9960
0.0041 12.96 3500 0.0209 0.9577 0.9748 0.9662 0.9960
0.0041 13.33 3600 0.0209 0.9603 0.9752 0.9677 0.9962
0.0041 13.7 3700 0.0215 0.9583 0.9752 0.9667 0.9961
0.0041 14.07 3800 0.0215 0.9577 0.9748 0.9662 0.9960
0.0041 14.44 3900 0.0213 0.9600 0.9759 0.9679 0.9962
0.003 14.81 4000 0.0213 0.9600 0.9759 0.9679 0.9962

Framework versions