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lmv2-g-dl-243-doc-09-13

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+ ---
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+ license: cc-by-nc-sa-4.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: lmv2-g-dl-243-doc-09-13
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # lmv2-g-dl-243-doc-09-13
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2104
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+ - Address Precision: 0.725
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+ - Address Recall: 0.7632
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+ - Address F1: 0.7436
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+ - Address Number: 38
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+ - Blood Group Precision: 0.8636
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+ - Blood Group Recall: 0.8636
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+ - Blood Group F1: 0.8636
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+ - Blood Group Number: 22
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+ - Date Of Issue Precision: 0.9787
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+ - Date Of Issue Recall: 0.92
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+ - Date Of Issue F1: 0.9485
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+ - Date Of Issue Number: 50
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+ - Dob Precision: 1.0
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+ - Dob Recall: 0.9773
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+ - Dob F1: 0.9885
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+ - Dob Number: 44
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+ - Driving Licence No Precision: 0.9796
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+ - Driving Licence No Recall: 1.0
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+ - Driving Licence No F1: 0.9897
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+ - Driving Licence No Number: 48
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+ - Name Precision: 0.9388
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+ - Name Recall: 0.9388
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+ - Name F1: 0.9388
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+ - Name Number: 49
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+ - S D W Name Precision: 0.9388
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+ - S D W Name Recall: 0.9583
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+ - S D W Name F1: 0.9485
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+ - S D W Name Number: 48
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+ - Valid Till Nt Precision: 0.7826
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+ - Valid Till Nt Recall: 0.8780
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+ - Valid Till Nt F1: 0.8276
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+ - Valid Till Nt Number: 41
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+ - Valid Till T Tr Precision: 0.9231
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+ - Valid Till T Tr Recall: 0.8571
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+ - Valid Till T Tr F1: 0.8889
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+ - Valid Till T Tr Number: 14
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+ - Overall Precision: 0.9078
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+ - Overall Recall: 0.9181
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+ - Overall F1: 0.9129
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+ - Overall Accuracy: 0.9763
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: constant
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Address Precision | Address Recall | Address F1 | Address Number | Blood Group Precision | Blood Group Recall | Blood Group F1 | Blood Group Number | Date Of Issue Precision | Date Of Issue Recall | Date Of Issue F1 | Date Of Issue Number | Dob Precision | Dob Recall | Dob F1 | Dob Number | Driving Licence No Precision | Driving Licence No Recall | Driving Licence No F1 | Driving Licence No Number | Name Precision | Name Recall | Name F1 | Name Number | S D W Name Precision | S D W Name Recall | S D W Name F1 | S D W Name Number | Valid Till Nt Precision | Valid Till Nt Recall | Valid Till Nt F1 | Valid Till Nt Number | Valid Till T Tr Precision | Valid Till T Tr Recall | Valid Till T Tr F1 | Valid Till T Tr Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------:|:----------:|:------:|:----------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:--------------:|:-----------:|:-------:|:-----------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 1.9194 | 1.0 | 194 | 1.3597 | 0.3099 | 0.5789 | 0.4037 | 38 | 0.0 | 0.0 | 0.0 | 22 | 0.3147 | 0.9 | 0.4663 | 50 | 0.0 | 0.0 | 0.0 | 44 | 0.1059 | 0.1875 | 0.1353 | 48 | 0.0246 | 0.0612 | 0.0351 | 49 | 0.0 | 0.0 | 0.0 | 48 | 0.0 | 0.0 | 0.0 | 41 | 0.0 | 0.0 | 0.0 | 14 | 0.1876 | 0.2232 | 0.2039 | 0.8582 |
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+ | 1.099 | 2.0 | 388 | 0.7767 | 0.5333 | 0.6316 | 0.5783 | 38 | 0.0 | 0.0 | 0.0 | 22 | 0.4667 | 0.98 | 0.6323 | 50 | 0.9773 | 0.9773 | 0.9773 | 44 | 0.9057 | 1.0 | 0.9505 | 48 | 0.3070 | 0.7143 | 0.4294 | 49 | 0.0 | 0.0 | 0.0 | 48 | 0.8182 | 0.2195 | 0.3462 | 41 | 0.0 | 0.0 | 0.0 | 14 | 0.5591 | 0.5876 | 0.5730 | 0.9016 |
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+ | 0.6398 | 3.0 | 582 | 0.4892 | 0.5532 | 0.6842 | 0.6118 | 38 | 0.0 | 0.0 | 0.0 | 22 | 1.0 | 0.94 | 0.9691 | 50 | 1.0 | 0.9091 | 0.9524 | 44 | 0.9412 | 1.0 | 0.9697 | 48 | 0.5538 | 0.7347 | 0.6316 | 49 | 0.5714 | 0.75 | 0.6486 | 48 | 0.6863 | 0.8537 | 0.7609 | 41 | 0.0 | 0.0 | 0.0 | 14 | 0.7363 | 0.7571 | 0.7465 | 0.9491 |
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+ | 0.4251 | 4.0 | 776 | 0.3770 | 0.4364 | 0.6316 | 0.5161 | 38 | 0.4706 | 0.3636 | 0.4103 | 22 | 1.0 | 0.9 | 0.9474 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9412 | 1.0 | 0.9697 | 48 | 0.92 | 0.9388 | 0.9293 | 49 | 0.9333 | 0.875 | 0.9032 | 48 | 0.6182 | 0.8293 | 0.7083 | 41 | 0.0 | 0.0 | 0.0 | 14 | 0.8033 | 0.8192 | 0.8112 | 0.9557 |
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+ | 0.304 | 5.0 | 970 | 0.2942 | 0.65 | 0.6842 | 0.6667 | 38 | 0.4643 | 0.5909 | 0.52 | 22 | 0.9796 | 0.96 | 0.9697 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.8727 | 1.0 | 0.9320 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9388 | 0.9583 | 0.9485 | 48 | 0.85 | 0.8293 | 0.8395 | 41 | 0.8 | 0.2857 | 0.4211 | 14 | 0.8603 | 0.8701 | 0.8652 | 0.9627 |
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+ | 0.2297 | 6.0 | 1164 | 0.2497 | 0.5854 | 0.6316 | 0.6076 | 38 | 0.5294 | 0.8182 | 0.6429 | 22 | 1.0 | 0.92 | 0.9583 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9231 | 1.0 | 0.9600 | 48 | 0.9149 | 0.8776 | 0.8958 | 49 | 0.9184 | 0.9375 | 0.9278 | 48 | 0.8462 | 0.8049 | 0.8250 | 41 | 0.7692 | 0.7143 | 0.7407 | 14 | 0.8516 | 0.8757 | 0.8635 | 0.9679 |
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+ | 0.1843 | 7.0 | 1358 | 0.2123 | 0.54 | 0.7105 | 0.6136 | 38 | 0.7778 | 0.9545 | 0.8571 | 22 | 0.9792 | 0.94 | 0.9592 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9348 | 0.8776 | 0.9053 | 49 | 0.9020 | 0.9583 | 0.9293 | 48 | 0.7609 | 0.8537 | 0.8046 | 41 | 0.8 | 0.5714 | 0.6667 | 14 | 0.8595 | 0.8983 | 0.8785 | 0.9696 |
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+ | 0.1455 | 8.0 | 1552 | 0.2166 | 0.6316 | 0.6316 | 0.6316 | 38 | 0.8077 | 0.9545 | 0.875 | 22 | 1.0 | 0.94 | 0.9691 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9216 | 0.9792 | 0.9495 | 48 | 0.9167 | 0.8980 | 0.9072 | 49 | 0.9167 | 0.9167 | 0.9167 | 48 | 0.7826 | 0.8780 | 0.8276 | 41 | 0.9286 | 0.9286 | 0.9286 | 14 | 0.8837 | 0.9011 | 0.8923 | 0.9696 |
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+ | 0.1262 | 9.0 | 1746 | 0.2060 | 0.5333 | 0.6316 | 0.5783 | 38 | 0.8333 | 0.9091 | 0.8696 | 22 | 0.96 | 0.96 | 0.96 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9216 | 0.9792 | 0.9495 | 48 | 0.9 | 0.9184 | 0.9091 | 49 | 0.9184 | 0.9375 | 0.9278 | 48 | 0.7826 | 0.8780 | 0.8276 | 41 | 0.5185 | 1.0 | 0.6829 | 14 | 0.8364 | 0.9096 | 0.8714 | 0.9661 |
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+ | 0.109 | 10.0 | 1940 | 0.1912 | 0.6154 | 0.6316 | 0.6234 | 38 | 0.7692 | 0.9091 | 0.8333 | 22 | 0.9792 | 0.94 | 0.9592 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9362 | 0.9167 | 0.9263 | 48 | 0.8537 | 0.8537 | 0.8537 | 41 | 0.9333 | 1.0 | 0.9655 | 14 | 0.8992 | 0.9068 | 0.9030 | 0.9725 |
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+ | 0.0911 | 11.0 | 2134 | 0.2063 | 0.5897 | 0.6053 | 0.5974 | 38 | 0.8 | 0.9091 | 0.8511 | 22 | 0.9412 | 0.96 | 0.9505 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9412 | 1.0 | 0.9697 | 48 | 0.9184 | 0.9184 | 0.9184 | 49 | 0.9375 | 0.9375 | 0.9375 | 48 | 0.8 | 0.8780 | 0.8372 | 41 | 0.8235 | 1.0 | 0.9032 | 14 | 0.875 | 0.9096 | 0.8920 | 0.9690 |
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+ | 0.0771 | 12.0 | 2328 | 0.2262 | 0.525 | 0.5526 | 0.5385 | 38 | 0.8333 | 0.9091 | 0.8696 | 22 | 1.0 | 0.98 | 0.9899 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9184 | 0.9375 | 0.9278 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9375 | 0.9375 | 0.9375 | 48 | 0.8537 | 0.8537 | 0.8537 | 41 | 0.8571 | 0.8571 | 0.8571 | 14 | 0.8852 | 0.8927 | 0.8889 | 0.9638 |
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+ | 0.0753 | 13.0 | 2522 | 0.2170 | 0.5714 | 0.6316 | 0.6 | 38 | 0.8 | 0.9091 | 0.8511 | 22 | 0.9796 | 0.96 | 0.9697 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9412 | 1.0 | 0.9697 | 48 | 0.9375 | 0.9184 | 0.9278 | 49 | 0.9574 | 0.9375 | 0.9474 | 48 | 0.875 | 0.8537 | 0.8642 | 41 | 0.7059 | 0.8571 | 0.7742 | 14 | 0.8840 | 0.9040 | 0.8939 | 0.9673 |
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+ | 0.0676 | 14.0 | 2716 | 0.2148 | 0.5610 | 0.6053 | 0.5823 | 38 | 0.8261 | 0.8636 | 0.8444 | 22 | 0.9245 | 0.98 | 0.9515 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.96 | 1.0 | 0.9796 | 48 | 0.9362 | 0.8980 | 0.9167 | 49 | 0.9130 | 0.875 | 0.8936 | 48 | 0.8182 | 0.8780 | 0.8471 | 41 | 0.9333 | 1.0 | 0.9655 | 14 | 0.8785 | 0.8983 | 0.8883 | 0.9670 |
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+ | 0.0588 | 15.0 | 2910 | 0.2140 | 0.65 | 0.6842 | 0.6667 | 38 | 0.7241 | 0.9545 | 0.8235 | 22 | 0.9792 | 0.94 | 0.9592 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9412 | 1.0 | 0.9697 | 48 | 0.8824 | 0.9184 | 0.9 | 49 | 0.9130 | 0.875 | 0.8936 | 48 | 0.8 | 0.8780 | 0.8372 | 41 | 0.9286 | 0.9286 | 0.9286 | 14 | 0.8747 | 0.9068 | 0.8904 | 0.9690 |
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+ | 0.0592 | 16.0 | 3104 | 0.2353 | 0.6410 | 0.6579 | 0.6494 | 38 | 0.75 | 0.9545 | 0.84 | 22 | 0.9767 | 0.84 | 0.9032 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9362 | 0.8980 | 0.9167 | 49 | 0.9574 | 0.9375 | 0.9474 | 48 | 0.8571 | 0.8780 | 0.8675 | 41 | 0.9333 | 1.0 | 0.9655 | 14 | 0.9008 | 0.8983 | 0.8996 | 0.9664 |
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+ | 0.0461 | 17.0 | 3298 | 0.2137 | 0.5714 | 0.6316 | 0.6 | 38 | 0.7143 | 0.9091 | 0.8 | 22 | 0.9057 | 0.96 | 0.9320 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9184 | 0.9375 | 0.9278 | 48 | 0.8571 | 0.8780 | 0.8675 | 41 | 0.7368 | 1.0 | 0.8485 | 14 | 0.8663 | 0.9153 | 0.8901 | 0.9685 |
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+ | 0.0424 | 18.0 | 3492 | 0.2057 | 0.5610 | 0.6053 | 0.5823 | 38 | 0.84 | 0.9545 | 0.8936 | 22 | 0.9423 | 0.98 | 0.9608 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9565 | 0.9167 | 0.9362 | 48 | 0.8095 | 0.8293 | 0.8193 | 41 | 0.8667 | 0.9286 | 0.8966 | 14 | 0.8867 | 0.9068 | 0.8966 | 0.9708 |
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+ | 0.0389 | 19.0 | 3686 | 0.2400 | 0.6098 | 0.6579 | 0.6329 | 38 | 0.8 | 0.9091 | 0.8511 | 22 | 0.9574 | 0.9 | 0.9278 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.86 | 0.8776 | 0.8687 | 49 | 0.8980 | 0.9167 | 0.9072 | 48 | 0.8537 | 0.8537 | 0.8537 | 41 | 0.9167 | 0.7857 | 0.8462 | 14 | 0.8796 | 0.8870 | 0.8833 | 0.9670 |
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+ | 0.0375 | 20.0 | 3880 | 0.2258 | 0.6341 | 0.6842 | 0.6582 | 38 | 0.8636 | 0.8636 | 0.8636 | 22 | 1.0 | 0.96 | 0.9796 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9565 | 0.9167 | 0.9362 | 48 | 0.8718 | 0.8293 | 0.8500 | 41 | 0.75 | 0.8571 | 0.8000 | 14 | 0.9065 | 0.9040 | 0.9052 | 0.9693 |
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+ | 0.036 | 21.0 | 4074 | 0.2686 | 0.5952 | 0.6579 | 0.625 | 38 | 0.7778 | 0.9545 | 0.8571 | 22 | 1.0 | 0.96 | 0.9796 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9362 | 0.8980 | 0.9167 | 49 | 0.9565 | 0.9167 | 0.9362 | 48 | 0.8684 | 0.8049 | 0.8354 | 41 | 0.7059 | 0.8571 | 0.7742 | 14 | 0.8908 | 0.8983 | 0.8945 | 0.9644 |
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+ | 0.0321 | 22.0 | 4268 | 0.2102 | 0.6923 | 0.7105 | 0.7013 | 38 | 0.7778 | 0.9545 | 0.8571 | 22 | 0.96 | 0.96 | 0.96 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.92 | 0.9388 | 0.9293 | 49 | 0.9362 | 0.9167 | 0.9263 | 48 | 0.8182 | 0.8780 | 0.8471 | 41 | 0.8571 | 0.8571 | 0.8571 | 14 | 0.8953 | 0.9181 | 0.9066 | 0.9722 |
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+ | 0.0244 | 23.0 | 4462 | 0.2432 | 0.6279 | 0.7105 | 0.6667 | 38 | 0.8 | 0.9091 | 0.8511 | 22 | 1.0 | 0.86 | 0.9247 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9362 | 0.9167 | 0.9263 | 48 | 0.7955 | 0.8537 | 0.8235 | 41 | 0.9091 | 0.7143 | 0.8 | 14 | 0.8927 | 0.8927 | 0.8927 | 0.9676 |
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+ | 0.0217 | 24.0 | 4656 | 0.2290 | 0.6923 | 0.7105 | 0.7013 | 38 | 0.8261 | 0.8636 | 0.8444 | 22 | 1.0 | 0.92 | 0.9583 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9375 | 0.9375 | 0.9375 | 48 | 0.8333 | 0.8537 | 0.8434 | 41 | 0.9167 | 0.7857 | 0.8462 | 14 | 0.9117 | 0.9040 | 0.9078 | 0.9728 |
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+ | 0.0215 | 25.0 | 4850 | 0.2677 | 0.5897 | 0.6053 | 0.5974 | 38 | 0.7778 | 0.9545 | 0.8571 | 22 | 0.9592 | 0.94 | 0.9495 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9375 | 0.9375 | 0.9375 | 48 | 0.7955 | 0.8537 | 0.8235 | 41 | 0.7 | 1.0 | 0.8235 | 14 | 0.875 | 0.9096 | 0.8920 | 0.9676 |
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+ | 0.0258 | 26.0 | 5044 | 0.2356 | 0.6341 | 0.6842 | 0.6582 | 38 | 0.7692 | 0.9091 | 0.8333 | 22 | 0.9796 | 0.96 | 0.9697 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.8980 | 0.9167 | 0.9072 | 48 | 0.7727 | 0.8293 | 0.8000 | 41 | 0.6923 | 0.6429 | 0.6667 | 14 | 0.8760 | 0.8983 | 0.8870 | 0.9696 |
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+ | 0.0191 | 27.0 | 5238 | 0.2115 | 0.625 | 0.6579 | 0.6410 | 38 | 0.8696 | 0.9091 | 0.8889 | 22 | 0.9792 | 0.94 | 0.9592 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9375 | 0.9375 | 0.9375 | 48 | 0.8571 | 0.8780 | 0.8675 | 41 | 0.8 | 0.8571 | 0.8276 | 14 | 0.9020 | 0.9096 | 0.9058 | 0.9751 |
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+ | 0.0238 | 28.0 | 5432 | 0.2104 | 0.725 | 0.7632 | 0.7436 | 38 | 0.8636 | 0.8636 | 0.8636 | 22 | 0.9787 | 0.92 | 0.9485 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9388 | 0.9583 | 0.9485 | 48 | 0.7826 | 0.8780 | 0.8276 | 41 | 0.9231 | 0.8571 | 0.8889 | 14 | 0.9078 | 0.9181 | 0.9129 | 0.9763 |
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+ | 0.0282 | 29.0 | 5626 | 0.2352 | 0.5238 | 0.5789 | 0.5500 | 38 | 0.8696 | 0.9091 | 0.8889 | 22 | 0.9778 | 0.88 | 0.9263 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9362 | 0.9167 | 0.9263 | 48 | 0.7609 | 0.8537 | 0.8046 | 41 | 0.75 | 0.8571 | 0.8000 | 14 | 0.8722 | 0.8870 | 0.8796 | 0.9705 |
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+ | 0.0157 | 30.0 | 5820 | 0.2614 | 0.6190 | 0.6842 | 0.6500 | 38 | 0.84 | 0.9545 | 0.8936 | 22 | 1.0 | 0.92 | 0.9583 | 50 | 1.0 | 0.9773 | 0.9885 | 44 | 0.9796 | 1.0 | 0.9897 | 48 | 0.9388 | 0.9388 | 0.9388 | 49 | 0.9583 | 0.9583 | 0.9583 | 48 | 0.72 | 0.8780 | 0.7912 | 41 | 0.7059 | 0.8571 | 0.7742 | 14 | 0.8780 | 0.9153 | 0.8963 | 0.9688 |
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+
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+ ### Framework versions
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+
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+ - Transformers 4.22.0.dev0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.2.2
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+ - Tokenizers 0.12.1