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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
model-index:
- name: lmv2-2022-05-24
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lmv2-2022-05-24
This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0484
- Address Precision: 0.9474
- Address Recall: 1.0
- Address F1: 0.9730
- Address Number: 18
- Business Name Precision: 1.0
- Business Name Recall: 1.0
- Business Name F1: 1.0
- Business Name Number: 13
- City State Zip Code Precision: 0.8947
- City State Zip Code Recall: 0.8947
- City State Zip Code F1: 0.8947
- City State Zip Code Number: 19
- Ein Precision: 1.0
- Ein Recall: 1.0
- Ein F1: 1.0
- Ein Number: 4
- List Account Number Precision: 0.6
- List Account Number Recall: 0.75
- List Account Number F1: 0.6667
- List Account Number Number: 4
- Name Precision: 1.0
- Name Recall: 0.9444
- Name F1: 0.9714
- Name Number: 18
- Ssn Precision: 1.0
- Ssn Recall: 1.0
- Ssn F1: 1.0
- Ssn Number: 8
- Overall Precision: 0.9412
- Overall Recall: 0.9524
- Overall F1: 0.9467
- Overall Accuracy: 0.9979
## 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:
- learning_rate: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Address Precision | Address Recall | Address F1 | Address Number | Business Name Precision | Business Name Recall | Business Name F1 | Business Name Number | City State Zip Code Precision | City State Zip Code Recall | City State Zip Code F1 | City State Zip Code Number | Ein Precision | Ein Recall | Ein F1 | Ein Number | List Account Number Precision | List Account Number Recall | List Account Number F1 | List Account Number Number | Name Precision | Name Recall | Name F1 | Name Number | Ssn Precision | Ssn Recall | Ssn F1 | Ssn Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-------------:|:----------:|:------:|:----------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 1.9388 | 1.0 | 79 | 1.5568 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.0 | 0.0 | 0.0 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 8 | 0.0 | 0.0 | 0.0 | 0.9465 |
| 1.3777 | 2.0 | 158 | 1.1259 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.0 | 0.0 | 0.0 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 8 | 0.0 | 0.0 | 0.0 | 0.9465 |
| 0.9629 | 3.0 | 237 | 0.7497 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.0 | 0.0 | 0.0 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 8 | 0.0 | 0.0 | 0.0 | 0.9465 |
| 0.6292 | 4.0 | 316 | 0.4818 | 0.0 | 0.0 | 0.0 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.0 | 0.0 | 0.0 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 18 | 0.1944 | 0.875 | 0.3182 | 8 | 0.1944 | 0.0833 | 0.1167 | 0.9523 |
| 0.3952 | 5.0 | 395 | 0.2982 | 0.2424 | 0.8889 | 0.3810 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.1111 | 0.1053 | 0.1081 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 4 | 0.0 | 0.0 | 0.0 | 18 | 0.6364 | 0.875 | 0.7368 | 8 | 0.2632 | 0.2976 | 0.2793 | 0.9660 |
| 0.2675 | 6.0 | 474 | 0.2183 | 1.0 | 0.9444 | 0.9714 | 18 | 0.0 | 0.0 | 0.0 | 13 | 0.8824 | 0.7895 | 0.8333 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.1905 | 0.4444 | 0.2667 | 18 | 0.5714 | 1.0 | 0.7273 | 8 | 0.5204 | 0.6071 | 0.5604 | 0.9810 |
| 0.2095 | 7.0 | 553 | 0.1990 | 1.0 | 0.9444 | 0.9714 | 18 | 0.0833 | 0.0769 | 0.08 | 13 | 0.9375 | 0.7895 | 0.8571 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.75 | 0.75 | 0.75 | 4 | 0.2647 | 0.5 | 0.3462 | 18 | 0.1739 | 1.0 | 0.2963 | 8 | 0.4109 | 0.6310 | 0.4977 | 0.9762 |
| 0.1928 | 8.0 | 632 | 0.1704 | 1.0 | 0.9444 | 0.9714 | 18 | 0.3158 | 0.4615 | 0.3750 | 13 | 0.9412 | 0.8421 | 0.8889 | 19 | 0.0 | 0.0 | 0.0 | 4 | 1.0 | 0.75 | 0.8571 | 4 | 0.3214 | 0.5 | 0.3913 | 18 | 0.5385 | 0.875 | 0.6667 | 8 | 0.5979 | 0.6905 | 0.6409 | 0.9849 |
| 0.159 | 9.0 | 711 | 0.1339 | 1.0 | 0.9444 | 0.9714 | 18 | 0.45 | 0.6923 | 0.5455 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.25 | 0.75 | 0.375 | 4 | 0.375 | 0.5 | 0.4286 | 18 | 0.2308 | 0.375 | 0.2857 | 8 | 0.5577 | 0.6905 | 0.6170 | 0.9871 |
| 0.1314 | 10.0 | 790 | 0.1199 | 0.9444 | 0.9444 | 0.9444 | 18 | 0.8571 | 0.9231 | 0.8889 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.7895 | 0.8333 | 0.8108 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8372 | 0.8571 | 0.8471 | 0.9897 |
| 0.1143 | 11.0 | 869 | 0.1127 | 0.9444 | 0.9444 | 0.9444 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.9036 | 0.8929 | 0.8982 | 0.9903 |
| 0.1037 | 12.0 | 948 | 0.1039 | 0.85 | 0.9444 | 0.8947 | 18 | 0.9167 | 0.8462 | 0.8800 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.8889 | 0.8889 | 0.8889 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8471 | 0.8571 | 0.8521 | 0.9901 |
| 0.0925 | 13.0 | 1027 | 0.1124 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.75 | 0.75 | 0.75 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.5833 | 0.875 | 0.7000 | 8 | 0.9136 | 0.8810 | 0.8970 | 0.9904 |
| 0.0863 | 14.0 | 1106 | 0.1077 | 0.9444 | 0.9444 | 0.9444 | 18 | 0.7333 | 0.8462 | 0.7857 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.6154 | 1.0 | 0.7619 | 8 | 0.8488 | 0.8690 | 0.8588 | 0.9916 |
| 0.0845 | 15.0 | 1185 | 0.1035 | 0.9444 | 0.9444 | 0.9444 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9412 | 0.8421 | 0.8889 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.5833 | 0.875 | 0.7000 | 8 | 0.8902 | 0.8690 | 0.8795 | 0.9921 |
| 0.0735 | 16.0 | 1264 | 0.0866 | 0.6667 | 0.8889 | 0.7619 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8315 | 0.8810 | 0.8555 | 0.9918 |
| 0.0714 | 17.0 | 1343 | 0.0781 | 0.9444 | 0.9444 | 0.9444 | 18 | 1.0 | 0.9231 | 0.9600 | 13 | 0.9412 | 0.8421 | 0.8889 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.9012 | 0.8690 | 0.8848 | 0.9921 |
| 0.0656 | 18.0 | 1422 | 0.0816 | 0.8947 | 0.9444 | 0.9189 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.9444 | 0.9444 | 0.9444 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8824 | 0.8929 | 0.8876 | 0.9919 |
| 0.0602 | 19.0 | 1501 | 0.0770 | 0.8 | 0.8889 | 0.8421 | 18 | 0.8667 | 1.0 | 0.9286 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.9444 | 0.9444 | 0.9444 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8409 | 0.8810 | 0.8605 | 0.9912 |
| 0.0516 | 20.0 | 1580 | 0.0710 | 0.8095 | 0.9444 | 0.8718 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.8721 | 0.8929 | 0.8824 | 0.9919 |
| 0.0475 | 21.0 | 1659 | 0.0686 | 0.6667 | 1.0 | 0.8 | 18 | 0.5 | 0.6154 | 0.5517 | 13 | 0.9412 | 0.8421 | 0.8889 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 0.9412 | 0.8889 | 0.9143 | 18 | 0.6667 | 1.0 | 0.8 | 8 | 0.7340 | 0.8214 | 0.7753 | 0.9904 |
| 0.0431 | 22.0 | 1738 | 0.0715 | 0.8095 | 0.9444 | 0.8718 | 18 | 0.9286 | 1.0 | 0.9630 | 13 | 0.8421 | 0.8421 | 0.8421 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.75 | 0.75 | 0.75 | 4 | 0.9444 | 0.9444 | 0.9444 | 18 | 0.3529 | 0.75 | 0.48 | 8 | 0.7273 | 0.8571 | 0.7869 | 0.9933 |
| 0.0383 | 23.0 | 1817 | 0.0627 | 0.8947 | 0.9444 | 0.9189 | 18 | 0.9231 | 0.9231 | 0.9231 | 13 | 0.8947 | 0.8947 | 0.8947 | 19 | 0.0 | 0.0 | 0.0 | 4 | 0.75 | 0.75 | 0.75 | 4 | 1.0 | 0.8889 | 0.9412 | 18 | 0.5714 | 1.0 | 0.7273 | 8 | 0.8111 | 0.8690 | 0.8391 | 0.9961 |
| 0.0327 | 24.0 | 1896 | 0.0683 | 0.8095 | 0.9444 | 0.8718 | 18 | 0.6 | 0.9231 | 0.7273 | 13 | 0.8095 | 0.8947 | 0.8500 | 19 | 0.6 | 0.75 | 0.6667 | 4 | 0.75 | 0.75 | 0.75 | 4 | 0.9412 | 0.8889 | 0.9143 | 18 | 0.8889 | 1.0 | 0.9412 | 8 | 0.7835 | 0.9048 | 0.8398 | 0.9942 |
| 0.0292 | 25.0 | 1975 | 0.0674 | 0.8947 | 0.9444 | 0.9189 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.85 | 0.8947 | 0.8718 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 8 | 0.9186 | 0.9405 | 0.9294 | 0.9975 |
| 0.0269 | 26.0 | 2054 | 0.0691 | 0.85 | 0.9444 | 0.8947 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 8 | 0.9294 | 0.9405 | 0.9349 | 0.9976 |
| 0.024 | 27.0 | 2133 | 0.0484 | 0.9474 | 1.0 | 0.9730 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.8947 | 0.8947 | 0.8947 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 8 | 0.9412 | 0.9524 | 0.9467 | 0.9979 |
| 0.0221 | 28.0 | 2212 | 0.0619 | 0.85 | 0.9444 | 0.8947 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 8 | 0.9294 | 0.9405 | 0.9349 | 0.9976 |
| 0.0216 | 29.0 | 2291 | 0.0810 | 0.85 | 0.9444 | 0.8947 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 0.875 | 0.9333 | 8 | 0.9286 | 0.9286 | 0.9286 | 0.9960 |
| 0.0175 | 30.0 | 2370 | 0.0646 | 0.85 | 0.9444 | 0.8947 | 18 | 1.0 | 1.0 | 1.0 | 13 | 0.9444 | 0.8947 | 0.9189 | 19 | 1.0 | 1.0 | 1.0 | 4 | 0.6 | 0.75 | 0.6667 | 4 | 1.0 | 0.9444 | 0.9714 | 18 | 1.0 | 1.0 | 1.0 | 8 | 0.9294 | 0.9405 | 0.9349 | 0.9976 |
### Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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