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End of training
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README.md
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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@@ -47,96 +47,96 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-------:|:----:|:---------------:|
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### Framework versions
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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+
- Loss: 5.5645
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-------:|:----:|:---------------:|
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| 5.3224 | 0.2212 | 50 | 4.5586 |
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| 4.5246 | 0.4425 | 100 | 4.1173 |
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| 4.1619 | 0.6637 | 150 | 3.8601 |
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| 3.7534 | 0.8850 | 200 | 3.6319 |
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| 3.6105 | 1.1062 | 250 | 3.7778 |
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| 3.3319 | 1.3274 | 300 | 3.1775 |
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| 3.0645 | 1.5487 | 350 | 2.8592 |
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| 2.8209 | 1.7699 | 400 | 2.7744 |
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| 2.7174 | 1.9912 | 450 | 2.7408 |
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| 2.0437 | 2.2124 | 500 | 2.7848 |
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| 2.0063 | 2.4336 | 550 | 2.9319 |
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| 1.9314 | 2.6549 | 600 | 2.3084 |
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| 1.7939 | 2.8761 | 650 | 2.4124 |
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| 1.7613 | 3.0973 | 700 | 2.5776 |
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| 1.3099 | 3.3186 | 750 | 2.2375 |
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| 1.4457 | 3.5398 | 800 | 2.7229 |
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| 1.4964 | 3.7611 | 850 | 2.5109 |
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| 1.428 | 3.9823 | 900 | 2.4552 |
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| 0.9892 | 4.2035 | 950 | 3.2111 |
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| 1.0568 | 4.4248 | 1000 | 2.3875 |
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| 0.8754 | 4.6460 | 1050 | 2.8059 |
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| 0.8201 | 4.8673 | 1100 | 2.5949 |
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| 1.0239 | 5.0885 | 1150 | 2.8688 |
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| 0.7348 | 5.3097 | 1200 | 2.8210 |
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| 0.7866 | 5.5310 | 1250 | 2.4231 |
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| 0.5954 | 5.7522 | 1300 | 2.8619 |
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| 0.7299 | 5.9735 | 1350 | 2.8536 |
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| 0.5132 | 6.1947 | 1400 | 2.6224 |
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| 0.7035 | 6.4159 | 1450 | 3.2108 |
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| 0.5626 | 6.6372 | 1500 | 2.8695 |
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| 0.431 | 6.8584 | 1550 | 3.3508 |
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| 0.4354 | 7.0796 | 1600 | 3.4196 |
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| 0.3896 | 7.3009 | 1650 | 3.1219 |
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| 0.4899 | 7.5221 | 1700 | 3.0649 |
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| 0.5703 | 7.7434 | 1750 | 3.0621 |
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| 0.435 | 7.9646 | 1800 | 3.3686 |
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| 0.3251 | 8.1858 | 1850 | 3.2093 |
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| 0.2464 | 8.4071 | 1900 | 3.9491 |
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| 0.4524 | 8.6283 | 1950 | 3.4324 |
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| 0.5715 | 8.8496 | 2000 | 3.5811 |
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| 0.3552 | 9.0708 | 2050 | 3.9434 |
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| 0.1147 | 9.2920 | 2100 | 4.5776 |
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| 0.2613 | 9.5133 | 2150 | 4.0439 |
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| 0.5679 | 9.7345 | 2200 | 3.4187 |
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| 0.3372 | 9.9558 | 2250 | 3.3868 |
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| 0.3143 | 10.1770 | 2300 | 4.2051 |
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| 0.1989 | 10.3982 | 2350 | 3.7925 |
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| 0.1859 | 10.6195 | 2400 | 4.1932 |
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| 0.3882 | 10.8407 | 2450 | 4.1672 |
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| 0.1824 | 11.0619 | 2500 | 4.3516 |
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| 0.106 | 11.2832 | 2550 | 4.5112 |
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| 0.2096 | 11.5044 | 2600 | 4.3784 |
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| 0.1035 | 11.7257 | 2650 | 4.3866 |
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| 0.2113 | 11.9469 | 2700 | 4.1279 |
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| 0.2263 | 12.1681 | 2750 | 4.2749 |
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| 0.1014 | 12.3894 | 2800 | 4.5176 |
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| 0.1555 | 12.6106 | 2850 | 3.9479 |
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| 0.1732 | 12.8319 | 2900 | 4.2414 |
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| 0.1484 | 13.0531 | 2950 | 4.0296 |
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| 0.1051 | 13.2743 | 3000 | 4.5086 |
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| 0.1282 | 13.4956 | 3050 | 4.6194 |
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| 0.1471 | 13.7168 | 3100 | 4.6707 |
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| 0.1888 | 13.9381 | 3150 | 4.3906 |
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| 0.0723 | 14.1593 | 3200 | 4.9790 |
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| 0.0302 | 14.3805 | 3250 | 5.0363 |
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| 0.1599 | 14.6018 | 3300 | 4.8371 |
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| 0.1179 | 14.8230 | 3350 | 4.3327 |
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| 0.1128 | 15.0442 | 3400 | 5.0618 |
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| 0.0493 | 15.2655 | 3450 | 5.2469 |
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| 0.0341 | 15.4867 | 3500 | 5.3640 |
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| 0.0545 | 15.7080 | 3550 | 5.0736 |
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| 0.0883 | 15.9292 | 3600 | 5.1372 |
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| 0.0461 | 16.1504 | 3650 | 5.0354 |
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| 0.0244 | 16.3717 | 3700 | 5.4353 |
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| 0.0541 | 16.5929 | 3750 | 5.3114 |
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| 0.0164 | 16.8142 | 3800 | 5.4107 |
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| 0.0336 | 17.0354 | 3850 | 5.4258 |
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| 0.0483 | 17.2566 | 3900 | 5.3555 |
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| 0.0994 | 17.4779 | 3950 | 5.2090 |
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| 0.0351 | 17.6991 | 4000 | 5.3768 |
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| 0.0065 | 17.9204 | 4050 | 5.5076 |
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| 0.0053 | 18.1416 | 4100 | 5.4823 |
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| 0.0043 | 18.3628 | 4150 | 5.4850 |
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| 0.0452 | 18.5841 | 4200 | 5.4849 |
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| 0.0086 | 18.8053 | 4250 | 5.5881 |
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| 0.0322 | 19.0265 | 4300 | 5.5167 |
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| 0.0135 | 19.2478 | 4350 | 5.5502 |
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| 0.0229 | 19.4690 | 4400 | 5.5385 |
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| 0.042 | 19.6903 | 4450 | 5.5602 |
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| 0.0404 | 19.9115 | 4500 | 5.5645 |
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### Framework versions
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