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

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: 0.2104
- Address Precision: 0.725
- Address Recall: 0.7632
- Address F1: 0.7436
- Address Number: 38
- Blood Group Precision: 0.8636
- Blood Group Recall: 0.8636
- Blood Group F1: 0.8636
- Blood Group Number: 22
- Date Of Issue Precision: 0.9787
- Date Of Issue Recall: 0.92
- Date Of Issue F1: 0.9485
- Date Of Issue Number: 50
- Dob Precision: 1.0
- Dob Recall: 0.9773
- Dob F1: 0.9885
- Dob Number: 44
- Driving Licence No Precision: 0.9796
- Driving Licence No Recall: 1.0
- Driving Licence No F1: 0.9897
- Driving Licence No Number: 48
- Name Precision: 0.9388
- Name Recall: 0.9388
- Name F1: 0.9388
- Name Number: 49
- S D W Name Precision: 0.9388
- S D W Name Recall: 0.9583
- S D W Name F1: 0.9485
- S D W Name Number: 48
- Valid Till Nt Precision: 0.7826
- Valid Till Nt Recall: 0.8780
- Valid Till Nt F1: 0.8276
- Valid Till Nt Number: 41
- Valid Till T Tr Precision: 0.9231
- Valid Till T Tr Recall: 0.8571
- Valid Till T Tr F1: 0.8889
- Valid Till T Tr Number: 14
- Overall Precision: 0.9078
- Overall Recall: 0.9181
- Overall F1: 0.9129
- Overall Accuracy: 0.9763

## 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 | 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------:|:----------:|:------:|:----------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:--------------:|:-----------:|:-------:|:-----------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |
| 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           |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "lmv2-g-dl-243-doc-09-13", "results": []}]}
transformers pytorch tensorboard layoutlmv2 token-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

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


This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2104
* Address Precision: 0.725
* Address Recall: 0.7632
* Address F1: 0.7436
* Address Number: 38
* Blood Group Precision: 0.8636
* Blood Group Recall: 0.8636
* Blood Group F1: 0.8636
* Blood Group Number: 22
* Date Of Issue Precision: 0.9787
* Date Of Issue Recall: 0.92
* Date Of Issue F1: 0.9485
* Date Of Issue Number: 50
* Dob Precision: 1.0
* Dob Recall: 0.9773
* Dob F1: 0.9885
* Dob Number: 44
* Driving Licence No Precision: 0.9796
* Driving Licence No Recall: 1.0
* Driving Licence No F1: 0.9897
* Driving Licence No Number: 48
* Name Precision: 0.9388
* Name Recall: 0.9388
* Name F1: 0.9388
* Name Number: 49
* S D W Name Precision: 0.9388
* S D W Name Recall: 0.9583
* S D W Name F1: 0.9485
* S D W Name Number: 48
* Valid Till Nt Precision: 0.7826
* Valid Till Nt Recall: 0.8780
* Valid Till Nt F1: 0.8276
* Valid Till Nt Number: 41
* Valid Till T Tr Precision: 0.9231
* Valid Till T Tr Recall: 0.8571
* Valid Till T Tr F1: 0.8889
* Valid Till T Tr Number: 14
* Overall Precision: 0.9078
* Overall Recall: 0.9181
* Overall F1: 0.9129
* Overall Accuracy: 0.9763


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



### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### 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 ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.22.0.dev0
* Pytorch 1.12.1+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1