generated_from_trainer

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perioli_vgm_v7.3

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 0.38 100 0.1302 0.1887 0.0560 0.0864 0.9666
No log 0.75 200 0.0878 0.5105 0.5112 0.5108 0.9748
No log 1.13 300 0.0606 0.7148 0.5826 0.6420 0.9841
No log 1.5 400 0.0663 0.5834 0.7003 0.6365 0.9810
0.0962 1.88 500 0.0503 0.7165 0.7185 0.7175 0.9866
0.0962 2.26 600 0.0596 0.6521 0.7535 0.6992 0.9845
0.0962 2.63 700 0.0429 0.8021 0.7325 0.7657 0.9901
0.0962 3.01 800 0.0413 0.7520 0.7815 0.7665 0.9891
0.0962 3.38 900 0.0425 0.7517 0.7969 0.7736 0.9891
0.0267 3.76 1000 0.0337 0.8496 0.7913 0.8194 0.9922
0.0267 4.14 1100 0.0377 0.7894 0.8137 0.8014 0.9908
0.0267 4.51 1200 0.0334 0.8355 0.8249 0.8302 0.9925
0.0267 4.89 1300 0.0346 0.8338 0.8361 0.8350 0.9928
0.0267 5.26 1400 0.0360 0.8549 0.8249 0.8396 0.9930
0.0118 5.64 1500 0.0361 0.8580 0.8375 0.8476 0.9935
0.0118 6.02 1600 0.0371 0.8505 0.8445 0.8475 0.9934
0.0118 6.39 1700 0.0367 0.8358 0.8557 0.8457 0.9930
0.0118 6.77 1800 0.0364 0.8178 0.8361 0.8269 0.9924
0.0118 7.14 1900 0.0396 0.7893 0.8291 0.8087 0.9915
0.0075 7.52 2000 0.0374 0.8470 0.8529 0.8500 0.9934
0.0075 7.89 2100 0.0402 0.8229 0.8263 0.8246 0.9924
0.0075 8.27 2200 0.0400 0.8436 0.8613 0.8524 0.9937
0.0075 8.65 2300 0.0403 0.8288 0.8473 0.8380 0.9931
0.0075 9.02 2400 0.0380 0.8664 0.8627 0.8646 0.9941
0.0039 9.4 2500 0.0401 0.8351 0.8585 0.8467 0.9933
0.0039 9.77 2600 0.0398 0.8317 0.8445 0.8381 0.9929
0.0039 10.15 2700 0.0402 0.8506 0.8613 0.8559 0.9938
0.0039 10.53 2800 0.0396 0.8573 0.8754 0.8663 0.9940
0.0039 10.9 2900 0.0371 0.8766 0.8655 0.8710 0.9944
0.0023 11.28 3000 0.0394 0.8482 0.8529 0.8506 0.9936
0.0023 11.65 3100 0.0414 0.8359 0.8487 0.8423 0.9934
0.0023 12.03 3200 0.0412 0.8469 0.8599 0.8534 0.9938
0.0023 12.41 3300 0.0410 0.8524 0.8655 0.8589 0.9940
0.0023 12.78 3400 0.0415 0.8508 0.8543 0.8526 0.9939
0.0015 13.16 3500 0.0423 0.8267 0.8487 0.8376 0.9932
0.0015 13.53 3600 0.0416 0.8536 0.8571 0.8553 0.9940
0.0015 13.91 3700 0.0423 0.8497 0.8627 0.8562 0.9940
0.0015 14.29 3800 0.0419 0.8664 0.8627 0.8646 0.9944
0.0015 14.66 3900 0.0416 0.8615 0.8627 0.8621 0.9943
0.0009 15.04 4000 0.0417 0.8615 0.8627 0.8621 0.9943

Framework versions