generated_from_trainer

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rhenus_model

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 1.96 100 0.7818 0.0909 0.0042 0.0081 0.8569
No log 3.92 200 0.5681 0.2442 0.0886 0.1300 0.8708
No log 5.88 300 0.4568 0.2803 0.1857 0.2234 0.8913
No log 7.84 400 0.3759 0.5053 0.4051 0.4496 0.9196
0.5952 9.8 500 0.2987 0.6560 0.6034 0.6286 0.9456
0.5952 11.76 600 0.2585 0.6721 0.6920 0.6819 0.9456
0.5952 13.73 700 0.2016 0.7247 0.7553 0.7397 0.9595
0.5952 15.69 800 0.2053 0.704 0.7426 0.7228 0.9573
0.5952 17.65 900 0.1845 0.7782 0.7848 0.7815 0.9667
0.1097 19.61 1000 0.1917 0.75 0.7848 0.7670 0.9623
0.1097 21.57 1100 0.1897 0.8099 0.8270 0.8184 0.9695
0.1097 23.53 1200 0.1848 0.7901 0.8101 0.8 0.9684
0.1097 25.49 1300 0.1533 0.8016 0.8523 0.8262 0.9734
0.1097 27.45 1400 0.1534 0.8204 0.8481 0.8340 0.9750
0.0384 29.41 1500 0.1879 0.8024 0.8397 0.8206 0.9695
0.0384 31.37 1600 0.1550 0.816 0.8608 0.8378 0.9750
0.0384 33.33 1700 0.1598 0.8279 0.8523 0.8399 0.9756
0.0384 35.29 1800 0.1643 0.8148 0.8354 0.825 0.9728
0.0384 37.25 1900 0.1558 0.792 0.8354 0.8131 0.9728
0.02 39.22 2000 0.1699 0.7944 0.8312 0.8124 0.9717
0.02 41.18 2100 0.1558 0.8138 0.8481 0.8306 0.9750
0.02 43.14 2200 0.1566 0.8024 0.8397 0.8206 0.9728
0.02 45.1 2300 0.1617 0.8049 0.8354 0.8199 0.9734
0.02 47.06 2400 0.1571 0.8016 0.8354 0.8182 0.9723
0.014 49.02 2500 0.1560 0.8057 0.8397 0.8223 0.9734

Framework versions