generated_from_trainer

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perioli_vgm_v7.0

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 0.39 100 0.0929 0.5216 0.3690 0.4322 0.9771
No log 0.78 200 0.0626 0.6467 0.6056 0.6255 0.9829
No log 1.16 300 0.0489 0.7337 0.6590 0.6944 0.9873
No log 1.55 400 0.0364 0.7721 0.8015 0.7865 0.9907
0.0803 1.94 500 0.0331 0.8307 0.7990 0.8145 0.9917
0.0803 2.33 600 0.0346 0.8127 0.8168 0.8147 0.9915
0.0803 2.71 700 0.0356 0.7755 0.8524 0.8121 0.9909
0.0803 3.1 800 0.0335 0.8075 0.8753 0.8400 0.9926
0.0803 3.49 900 0.0290 0.8519 0.8779 0.8647 0.9943
0.0138 3.88 1000 0.0313 0.8321 0.8830 0.8568 0.9934
0.0138 4.26 1100 0.0295 0.8872 0.9008 0.8939 0.9949
0.0138 4.65 1200 0.0319 0.8313 0.8779 0.8540 0.9940
0.0138 5.04 1300 0.0285 0.8697 0.8830 0.8763 0.9947
0.0138 5.43 1400 0.0295 0.8875 0.9033 0.8953 0.9953
0.0049 5.81 1500 0.0305 0.9015 0.9084 0.9049 0.9954
0.0049 6.2 1600 0.0298 0.9003 0.8957 0.8980 0.9954
0.0049 6.59 1700 0.0285 0.9247 0.9059 0.9152 0.9959
0.0049 6.98 1800 0.0288 0.9158 0.9135 0.9146 0.9957
0.0049 7.36 1900 0.0269 0.9045 0.9160 0.9102 0.9963
0.0022 7.75 2000 0.0277 0.9102 0.9288 0.9194 0.9963
0.0022 8.14 2100 0.0288 0.91 0.9262 0.9180 0.9957
0.0022 8.53 2200 0.0279 0.9037 0.9313 0.9173 0.9955
0.0022 8.91 2300 0.0322 0.9054 0.9008 0.9031 0.9954
0.0022 9.3 2400 0.0317 0.8875 0.9237 0.9052 0.9951
0.0015 9.69 2500 0.0294 0.9005 0.9211 0.9107 0.9955
0.0015 10.08 2600 0.0325 0.8970 0.9084 0.9027 0.9954
0.0015 10.47 2700 0.0309 0.905 0.9211 0.9130 0.9958
0.0015 10.85 2800 0.0301 0.9118 0.9211 0.9165 0.9958
0.0015 11.24 2900 0.0287 0.9162 0.9186 0.9174 0.9961
0.0008 11.63 3000 0.0276 0.9258 0.9211 0.9235 0.9962
0.0008 12.02 3100 0.0309 0.9129 0.9338 0.9233 0.9960
0.0008 12.4 3200 0.0296 0.9173 0.9313 0.9242 0.9962
0.0008 12.79 3300 0.0295 0.9217 0.9288 0.9252 0.9962
0.0008 13.18 3400 0.0307 0.9190 0.9237 0.9213 0.9960
0.0004 13.57 3500 0.0301 0.9190 0.9237 0.9213 0.9961
0.0004 13.95 3600 0.0306 0.9237 0.9237 0.9237 0.9961
0.0004 14.34 3700 0.0306 0.9165 0.9211 0.9188 0.9960
0.0004 14.73 3800 0.0305 0.9215 0.9262 0.9239 0.9961
0.0004 15.12 3900 0.0305 0.9215 0.9262 0.9239 0.9961
0.0003 15.5 4000 0.0305 0.9215 0.9262 0.9239 0.9961

Framework versions