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# layoutlmv2-finetuned-cord_500

This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the cord-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2207
- Menu.cnt Precision: 1.0
- Menu.cnt Recall: 0.9867
- Menu.cnt F1: 0.9933
- Menu.cnt Number: 225
- Menu.discountprice Precision: 0.8889
- Menu.discountprice Recall: 0.8
- Menu.discountprice F1: 0.8421
- Menu.discountprice Number: 10
- Menu.etc Precision: 0.0
- Menu.etc Recall: 0.0
- Menu.etc F1: 0.0
- Menu.etc Number: 3
- Menu.itemsubtotal Precision: 0.0
- Menu.itemsubtotal Recall: 0.0
- Menu.itemsubtotal F1: 0.0
- Menu.itemsubtotal Number: 6
- Menu.nm Precision: 0.9764
- Menu.nm Recall: 0.9880
- Menu.nm F1: 0.9822
- Menu.nm Number: 251
- Menu.num Precision: 0.8462
- Menu.num Recall: 1.0
- Menu.num F1: 0.9167
- Menu.num Number: 11
- Menu.price Precision: 0.9723
- Menu.price Recall: 0.9919
- Menu.price F1: 0.9820
- Menu.price Number: 248
- Menu.sub Cnt Precision: 0.85
- Menu.sub Cnt Recall: 1.0
- Menu.sub Cnt F1: 0.9189
- Menu.sub Cnt Number: 17
- Menu.sub Nm Precision: 0.8421
- Menu.sub Nm Recall: 0.8649
- Menu.sub Nm F1: 0.8533
- Menu.sub Nm Number: 37
- Menu.sub Price Precision: 0.95
- Menu.sub Price Recall: 0.95
- Menu.sub Price F1: 0.9500
- Menu.sub Price Number: 20
- Menu.unitprice Precision: 0.9855
- Menu.unitprice Recall: 0.9855
- Menu.unitprice F1: 0.9855
- Menu.unitprice Number: 69
- Sub Total.discount Price Precision: 0.8571
- Sub Total.discount Price Recall: 0.8571
- Sub Total.discount Price F1: 0.8571
- Sub Total.discount Price Number: 7
- Sub Total.etc Precision: 0.9231
- Sub Total.etc Recall: 0.9231
- Sub Total.etc F1: 0.9231
- Sub Total.etc Number: 13
- Sub Total.service Price Precision: 1.0
- Sub Total.service Price Recall: 1.0
- Sub Total.service Price F1: 1.0
- Sub Total.service Price Number: 12
- Sub Total.subtotal Price Precision: 0.9714
- Sub Total.subtotal Price Recall: 0.9855
- Sub Total.subtotal Price F1: 0.9784
- Sub Total.subtotal Price Number: 69
- Sub Total.tax Price Precision: 1.0
- Sub Total.tax Price Recall: 1.0
- Sub Total.tax Price F1: 1.0
- Sub Total.tax Price Number: 47
- Total.cashprice Precision: 1.0
- Total.cashprice Recall: 0.9167
- Total.cashprice F1: 0.9565
- Total.cashprice Number: 72
- Total.changeprice Precision: 0.9672
- Total.changeprice Recall: 1.0
- Total.changeprice F1: 0.9833
- Total.changeprice Number: 59
- Total.creditcardprice Precision: 1.0
- Total.creditcardprice Recall: 0.9412
- Total.creditcardprice F1: 0.9697
- Total.creditcardprice Number: 17
- Total.emoneyprice Precision: 0.1667
- Total.emoneyprice Recall: 0.5
- Total.emoneyprice F1: 0.25
- Total.emoneyprice Number: 2
- Total.menuqty Cnt Precision: 0.9667
- Total.menuqty Cnt Recall: 1.0
- Total.menuqty Cnt F1: 0.9831
- Total.menuqty Cnt Number: 29
- Total.menutype Cnt Precision: 1.0
- Total.menutype Cnt Recall: 0.7143
- Total.menutype Cnt F1: 0.8333
- Total.menutype Cnt Number: 7
- Total.total Etc Precision: 0.0
- Total.total Etc Recall: 0.0
- Total.total Etc F1: 0.0
- Total.total Etc Number: 4
- Total.total Price Precision: 0.9709
- Total.total Price Recall: 0.9901
- Total.total Price F1: 0.9804
- Total.total Price Number: 101
- Overall Precision: 0.9627
- Overall Recall: 0.9671
- Overall F1: 0.9649
- Overall Accuracy: 0.9690

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Menu.cnt Precision | Menu.cnt Recall | Menu.cnt F1 | Menu.cnt Number | Menu.discountprice Precision | Menu.discountprice Recall | Menu.discountprice F1 | Menu.discountprice Number | Menu.etc Precision | Menu.etc Recall | Menu.etc F1 | Menu.etc Number | Menu.itemsubtotal Precision | Menu.itemsubtotal Recall | Menu.itemsubtotal F1 | Menu.itemsubtotal Number | Menu.nm Precision | Menu.nm Recall | Menu.nm F1 | Menu.nm Number | Menu.num Precision | Menu.num Recall | Menu.num F1 | Menu.num Number | Menu.price Precision | Menu.price Recall | Menu.price F1 | Menu.price Number | Menu.sub Cnt Precision | Menu.sub Cnt Recall | Menu.sub Cnt F1 | Menu.sub Cnt Number | Menu.sub Nm Precision | Menu.sub Nm Recall | Menu.sub Nm F1 | Menu.sub Nm Number | Menu.sub Price Precision | Menu.sub Price Recall | Menu.sub Price F1 | Menu.sub Price Number | Menu.unitprice Precision | Menu.unitprice Recall | Menu.unitprice F1 | Menu.unitprice Number | Sub Total.discount Price Precision | Sub Total.discount Price Recall | Sub Total.discount Price F1 | Sub Total.discount Price Number | Sub Total.etc Precision | Sub Total.etc Recall | Sub Total.etc F1 | Sub Total.etc Number | Sub Total.service Price Precision | Sub Total.service Price Recall | Sub Total.service Price F1 | Sub Total.service Price Number | Sub Total.subtotal Price Precision | Sub Total.subtotal Price Recall | Sub Total.subtotal Price F1 | Sub Total.subtotal Price Number | Sub Total.tax Price Precision | Sub Total.tax Price Recall | Sub Total.tax Price F1 | Sub Total.tax Price Number | Total.cashprice Precision | Total.cashprice Recall | Total.cashprice F1 | Total.cashprice Number | Total.changeprice Precision | Total.changeprice Recall | Total.changeprice F1 | Total.changeprice Number | Total.creditcardprice Precision | Total.creditcardprice Recall | Total.creditcardprice F1 | Total.creditcardprice Number | Total.emoneyprice Precision | Total.emoneyprice Recall | Total.emoneyprice F1 | Total.emoneyprice Number | Total.menuqty Cnt Precision | Total.menuqty Cnt Recall | Total.menuqty Cnt F1 | Total.menuqty Cnt Number | Total.menutype Cnt Precision | Total.menutype Cnt Recall | Total.menutype Cnt F1 | Total.menutype Cnt Number | Total.total Etc Precision | Total.total Etc Recall | Total.total Etc F1 | Total.total Etc Number | Total.total Price Precision | Total.total Price Recall | Total.total Price F1 | Total.total Price Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:------------------:|:---------------:|:-----------:|:---------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-----------------:|:--------------:|:----------:|:--------------:|:------------------:|:---------------:|:-----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:----------------------------------:|:-------------------------------:|:---------------------------:|:-------------------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:---------------------------------:|:------------------------------:|:--------------------------:|:------------------------------:|:----------------------------------:|:-------------------------------:|:---------------------------:|:-------------------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-------------------------------:|:----------------------------:|:------------------------:|:----------------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| No log        | 2.0   | 250  | 2.5018          | 0.85               | 0.9822          | 0.9113      | 225             | 0.0                          | 0.0                       | 0.0                   | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.8257            | 1.0            | 0.9045     | 251            | 0.0                | 0.0             | 0.0         | 11              | 0.8746               | 0.9839            | 0.9260        | 248               | 0.0                    | 0.0                 | 0.0             | 17                  | 0.0                   | 0.0                | 0.0            | 37                 | 0.0                      | 0.0                   | 0.0               | 20                    | 0.9296                   | 0.9565                | 0.9429            | 69                    | 0.0                                | 0.0                             | 0.0                         | 7                               | 0.0                     | 0.0                  | 0.0              | 13                   | 0.0                               | 0.0                            | 0.0                        | 12                             | 0.8108                             | 0.8696                          | 0.8392                      | 69                              | 0.4719                        | 0.8936                     | 0.6176                 | 47                         | 0.7683                    | 0.875                  | 0.8182             | 72                     | 0.8                         | 0.8814                   | 0.8387               | 59                       | 0.0                             | 0.0                          | 0.0                      | 17                           | 0.0                         | 0.0                      | 0.0                  | 2                        | 0.4138                      | 0.4138                   | 0.4138               | 29                       | 0.0                          | 0.0                       | 0.0                   | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.7323                      | 0.9208                   | 0.8158               | 101                      | 0.7983            | 0.8263         | 0.8121     | 0.8255           |
| 2.6537        | 4.0   | 500  | 1.3952          | 0.8805             | 0.9822          | 0.9286      | 225             | 0.7273                       | 0.8                       | 0.7619                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.8817            | 0.9801         | 0.9283     | 251            | 1.0                | 1.0             | 1.0         | 11              | 0.8547               | 0.9960            | 0.9199        | 248               | 0.0                    | 0.0                 | 0.0             | 17                  | 0.4444                | 0.1081             | 0.1739         | 37                 | 0.0                      | 0.0                   | 0.0               | 20                    | 0.8608                   | 0.9855                | 0.9189            | 69                    | 0.0                                | 0.0                             | 0.0                         | 7                               | 0.0                     | 0.0                  | 0.0              | 13                   | 0.3438                            | 0.9167                         | 0.5                        | 12                             | 0.8919                             | 0.9565                          | 0.9231                      | 69                              | 0.88                          | 0.9362                     | 0.9072                 | 47                         | 1.0                       | 0.875                  | 0.9333             | 72                     | 0.9483                      | 0.9322                   | 0.9402               | 59                       | 0.6522                          | 0.8824                       | 0.75                     | 17                           | 0.0                         | 0.0                      | 0.0                  | 2                        | 0.8286                      | 1.0                      | 0.9062               | 29                       | 0.0                          | 0.0                       | 0.0                   | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9684                      | 0.9109                   | 0.9388               | 101                      | 0.8632            | 0.8832         | 0.8731     | 0.8947           |
| 2.6537        | 6.0   | 750  | 0.7646          | 0.9170             | 0.9822          | 0.9485      | 225             | 0.5556                       | 0.5                       | 0.5263                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9537            | 0.9841         | 0.9686     | 251            | 1.0                | 1.0             | 1.0         | 11              | 0.9385               | 0.9839            | 0.9606        | 248               | 0.0                    | 0.0                 | 0.0             | 17                  | 0.8                   | 0.8649             | 0.8312         | 37                 | 1.0                      | 0.55                  | 0.7097            | 20                    | 0.9306                   | 0.9710                | 0.9504            | 69                    | 0.75                               | 0.8571                          | 0.8000                      | 7                               | 0.6667                  | 0.7692               | 0.7143           | 13                   | 0.8571                            | 1.0                            | 0.9231                     | 12                             | 0.9067                             | 0.9855                          | 0.9444                      | 69                              | 0.9787                        | 0.9787                     | 0.9787                 | 47                         | 1.0                       | 0.9167                 | 0.9565             | 72                     | 0.9516                      | 1.0                      | 0.9752               | 59                       | 0.7619                          | 0.9412                       | 0.8421                   | 17                           | 0.0                         | 0.0                      | 0.0                  | 2                        | 0.7632                      | 1.0                      | 0.8657               | 29                       | 0.0                          | 0.0                       | 0.0                   | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.97                        | 0.9604                   | 0.9652               | 101                      | 0.9244            | 0.9334         | 0.9289     | 0.9435           |
| 0.8368        | 8.0   | 1000 | 0.4986          | 0.9567             | 0.9822          | 0.9693      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9764            | 0.9880         | 0.9822     | 251            | 0.7333             | 1.0             | 0.8462      | 11              | 0.9648               | 0.9960            | 0.9802        | 248               | 1.0                    | 0.6471              | 0.7857          | 17                  | 0.8718                | 0.9189             | 0.8947         | 37                 | 1.0                      | 0.85                  | 0.9189            | 20                    | 0.9718                   | 1.0                   | 0.9857            | 69                    | 0.5556                             | 0.7143                          | 0.6250                      | 7                               | 0.8889                  | 0.6154               | 0.7273           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.8831                             | 0.9855                          | 0.9315                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 1.0                       | 0.8889                 | 0.9412             | 72                     | 0.9831                      | 0.9831                   | 0.9831               | 59                       | 0.5333                          | 0.9412                       | 0.6809                   | 17                           | 0.0                         | 0.0                      | 0.0                  | 2                        | 0.8056                      | 1.0                      | 0.8923               | 29                       | 0.0                          | 0.0                       | 0.0                   | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9694                      | 0.9406                   | 0.9548               | 101                      | 0.9420            | 0.9484         | 0.9452     | 0.9520           |
| 0.8368        | 10.0  | 1250 | 0.3597          | 0.9528             | 0.9867          | 0.9694      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9688            | 0.9880         | 0.9783     | 251            | 0.7333             | 1.0             | 0.8462      | 11              | 0.9462               | 0.9919            | 0.9685        | 248               | 1.0                    | 0.5294              | 0.6923          | 17                  | 0.825                 | 0.8919             | 0.8571         | 37                 | 1.0                      | 0.65                  | 0.7879            | 20                    | 0.9718                   | 1.0                   | 0.9857            | 69                    | 1.0                                | 1.0                             | 1.0                         | 7                               | 0.8667                  | 1.0                  | 0.9286           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9324                             | 1.0                             | 0.9650                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 1.0                       | 0.9306                 | 0.9640             | 72                     | 0.9516                      | 1.0                      | 0.9752               | 59                       | 0.8889                          | 0.9412                       | 0.9143                   | 17                           | 0.25                        | 0.5                      | 0.3333               | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9898                      | 0.9604                   | 0.9749               | 101                      | 0.9524            | 0.9581         | 0.9552     | 0.9660           |
| 0.3287        | 12.0  | 1500 | 0.3021          | 0.9864             | 0.9644          | 0.9753      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9839            | 0.9761         | 0.98       | 251            | 0.7333             | 1.0             | 0.8462      | 11              | 0.9755               | 0.9637            | 0.9696        | 248               | 0.7727                 | 1.0                 | 0.8718          | 17                  | 0.7556                | 0.9189             | 0.8293         | 37                 | 0.7917                   | 0.95                  | 0.8636            | 20                    | 0.9855                   | 0.9855                | 0.9855            | 69                    | 1.0                                | 1.0                             | 1.0                         | 7                               | 0.8667                  | 1.0                  | 0.9286           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.8947                             | 0.9855                          | 0.9379                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 1.0                       | 0.9306                 | 0.9640             | 72                     | 0.9516                      | 1.0                      | 0.9752               | 59                       | 0.8889                          | 0.9412                       | 0.9143                   | 17                           | 0.5                         | 1.0                      | 0.6667               | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9802                      | 0.9802                   | 0.9802               | 101                      | 0.9553            | 0.9588         | 0.9570     | 0.9652           |
| 0.3287        | 14.0  | 1750 | 0.2756          | 0.9825             | 0.9956          | 0.9890      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9650            | 0.9880         | 0.9764     | 251            | 0.9167             | 1.0             | 0.9565      | 11              | 0.9762               | 0.9919            | 0.9840        | 248               | 1.0                    | 0.8824              | 0.9375          | 17                  | 0.8889                | 0.8649             | 0.8767         | 37                 | 0.95                     | 0.95                  | 0.9500            | 20                    | 0.9855                   | 0.9855                | 0.9855            | 69                    | 0.875                              | 1.0                             | 0.9333                      | 7                               | 0.9091                  | 0.7692               | 0.8333           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9189                             | 0.9855                          | 0.9510                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 1.0                       | 0.9306                 | 0.9640             | 72                     | 0.9516                      | 1.0                      | 0.9752               | 59                       | 0.9412                          | 0.9412                       | 0.9412                   | 17                           | 0.3333                      | 0.5                      | 0.4                  | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9612                      | 0.9802                   | 0.9706               | 101                      | 0.9648            | 0.9656         | 0.9652     | 0.9656           |
| 0.1835        | 16.0  | 2000 | 0.2440          | 0.9955             | 0.9867          | 0.9911      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9688            | 0.9880         | 0.9783     | 251            | 0.9167             | 1.0             | 0.9565      | 11              | 0.9762               | 0.9919            | 0.9840        | 248               | 0.85                   | 1.0                 | 0.9189          | 17                  | 0.8684                | 0.8919             | 0.88           | 37                 | 1.0                      | 0.95                  | 0.9744            | 20                    | 0.9853                   | 0.9710                | 0.9781            | 69                    | 1.0                                | 1.0                             | 1.0                         | 7                               | 0.9286                  | 1.0                  | 0.9630           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9444                             | 0.9855                          | 0.9645                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 0.9851                    | 0.9167                 | 0.9496             | 72                     | 0.9672                      | 1.0                      | 0.9833               | 59                       | 0.9412                          | 0.9412                       | 0.9412                   | 17                           | 0.4                         | 1.0                      | 0.5714               | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9712                      | 1.0                      | 0.9854               | 101                      | 0.9679            | 0.9693         | 0.9686     | 0.9720           |
| 0.1835        | 18.0  | 2250 | 0.2300          | 0.9912             | 0.9956          | 0.9933      | 225             | 0.8                          | 0.8                       | 0.8000                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9764            | 0.9880         | 0.9822     | 251            | 0.7857             | 1.0             | 0.88        | 11              | 0.9762               | 0.9919            | 0.9840        | 248               | 0.9444                 | 1.0                 | 0.9714          | 17                  | 0.8205                | 0.8649             | 0.8421         | 37                 | 0.95                     | 0.95                  | 0.9500            | 20                    | 0.9855                   | 0.9855                | 0.9855            | 69                    | 0.8571                             | 0.8571                          | 0.8571                      | 7                               | 0.9231                  | 0.9231               | 0.9231           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9577                             | 0.9855                          | 0.9714                      | 69                              | 1.0                           | 1.0                        | 1.0                    | 47                         | 1.0                       | 0.9028                 | 0.9489             | 72                     | 0.9672                      | 1.0                      | 0.9833               | 59                       | 0.9412                          | 0.9412                       | 0.9412                   | 17                           | 0.1667                      | 0.5                      | 0.25                 | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9709                      | 0.9901                   | 0.9804               | 101                      | 0.9628            | 0.9678         | 0.9653     | 0.9690           |
| 0.1239        | 20.0  | 2500 | 0.2151          | 1.0                | 0.9867          | 0.9933      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9724            | 0.9841         | 0.9782     | 251            | 0.8462             | 1.0             | 0.9167      | 11              | 0.98                 | 0.9879            | 0.9839        | 248               | 0.85                   | 1.0                 | 0.9189          | 17                  | 0.85                  | 0.9189             | 0.8831         | 37                 | 0.8636                   | 0.95                  | 0.9048            | 20                    | 0.9855                   | 0.9855                | 0.9855            | 69                    | 0.8571                             | 0.8571                          | 0.8571                      | 7                               | 0.9231                  | 0.9231               | 0.9231           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9444                             | 0.9855                          | 0.9645                      | 69                              | 1.0                           | 0.9787                     | 0.9892                 | 47                         | 1.0                       | 0.9167                 | 0.9565             | 72                     | 0.9672                      | 1.0                      | 0.9833               | 59                       | 0.9412                          | 0.9412                       | 0.9412                   | 17                           | 0.1667                      | 0.5                      | 0.25                 | 2                        | 1.0                         | 0.9655                   | 0.9825               | 29                       | 0.8571                       | 0.8571                    | 0.8571                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9709                      | 0.9901                   | 0.9804               | 101                      | 0.9620            | 0.9663         | 0.9642     | 0.9690           |
| 0.1239        | 22.0  | 2750 | nan             | 1.0                | 0.9778          | 0.9888      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9723            | 0.9801         | 0.9762     | 251            | 0.8462             | 1.0             | 0.9167      | 11              | 0.9721               | 0.9839            | 0.9780        | 248               | 0.85                   | 1.0                 | 0.9189          | 17                  | 0.8611                | 0.8378             | 0.8493         | 37                 | 0.95                     | 0.95                  | 0.9500            | 20                    | 0.9851                   | 0.9565                | 0.9706            | 69                    | 0.8333                             | 0.7143                          | 0.7692                      | 7                               | 0.9231                  | 0.9231               | 0.9231           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9710                             | 0.9710                          | 0.9710                      | 69                              | 1.0                           | 1.0                        | 1.0                    | 47                         | 1.0                       | 0.9028                 | 0.9489             | 72                     | 0.9667                      | 0.9831                   | 0.9748               | 59                       | 1.0                             | 0.9412                       | 0.9697                   | 17                           | 0.1667                      | 0.5                      | 0.25                 | 2                        | 1.0                         | 1.0                      | 1.0                  | 29                       | 1.0                          | 0.8571                    | 0.9231                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9706                      | 0.9802                   | 0.9754               | 101                      | 0.9624            | 0.9573         | 0.9598     | 0.9575           |
| 0.1008        | 24.0  | 3000 | 0.2207          | 1.0                | 0.9867          | 0.9933      | 225             | 0.8889                       | 0.8                       | 0.8421                | 10                        | 0.0                | 0.0             | 0.0         | 3               | 0.0                         | 0.0                      | 0.0                  | 6                        | 0.9764            | 0.9880         | 0.9822     | 251            | 0.8462             | 1.0             | 0.9167      | 11              | 0.9723               | 0.9919            | 0.9820        | 248               | 0.85                   | 1.0                 | 0.9189          | 17                  | 0.8421                | 0.8649             | 0.8533         | 37                 | 0.95                     | 0.95                  | 0.9500            | 20                    | 0.9855                   | 0.9855                | 0.9855            | 69                    | 0.8571                             | 0.8571                          | 0.8571                      | 7                               | 0.9231                  | 0.9231               | 0.9231           | 13                   | 1.0                               | 1.0                            | 1.0                        | 12                             | 0.9714                             | 0.9855                          | 0.9784                      | 69                              | 1.0                           | 1.0                        | 1.0                    | 47                         | 1.0                       | 0.9167                 | 0.9565             | 72                     | 0.9672                      | 1.0                      | 0.9833               | 59                       | 1.0                             | 0.9412                       | 0.9697                   | 17                           | 0.1667                      | 0.5                      | 0.25                 | 2                        | 0.9667                      | 1.0                      | 0.9831               | 29                       | 1.0                          | 0.7143                    | 0.8333                | 7                         | 0.0                       | 0.0                    | 0.0                | 4                      | 0.9709                      | 0.9901                   | 0.9804               | 101                      | 0.9627            | 0.9671         | 0.9649     | 0.9690           |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.10.0+cu111
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["cord-layoutlmv3"], "model-index": [{"name": "layoutlmv2-finetuned-cord_500", "results": []}]}
transformers pytorch tensorboard layoutlmv2 token-classification generated_from_trainer dataset:cord-layoutlmv3 license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #dataset-cord-layoutlmv3 #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv2-finetuned-cord\_500
==============================


This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on the cord-layoutlmv3 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2207
* URL Precision: 1.0
* URL Recall: 0.9867
* URL F1: 0.9933
* URL Number: 225
* Menu.discountprice Precision: 0.8889
* Menu.discountprice Recall: 0.8
* Menu.discountprice F1: 0.8421
* Menu.discountprice Number: 10
* URL Precision: 0.0
* URL Recall: 0.0
* URL F1: 0.0
* URL Number: 3
* Menu.itemsubtotal Precision: 0.0
* Menu.itemsubtotal Recall: 0.0
* Menu.itemsubtotal F1: 0.0
* Menu.itemsubtotal Number: 6
* URL Precision: 0.9764
* URL Recall: 0.9880
* URL F1: 0.9822
* URL Number: 251
* URL Precision: 0.8462
* URL Recall: 1.0
* URL F1: 0.9167
* URL Number: 11
* URL Precision: 0.9723
* URL Recall: 0.9919
* URL F1: 0.9820
* URL Number: 248
* URL Cnt Precision: 0.85
* URL Cnt Recall: 1.0
* URL Cnt F1: 0.9189
* URL Cnt Number: 17
* URL Nm Precision: 0.8421
* URL Nm Recall: 0.8649
* URL Nm F1: 0.8533
* URL Nm Number: 37
* URL Price Precision: 0.95
* URL Price Recall: 0.95
* URL Price F1: 0.9500
* URL Price Number: 20
* Menu.unitprice Precision: 0.9855
* Menu.unitprice Recall: 0.9855
* Menu.unitprice F1: 0.9855
* Menu.unitprice Number: 69
* Sub Total.discount Price Precision: 0.8571
* Sub Total.discount Price Recall: 0.8571
* Sub Total.discount Price F1: 0.8571
* Sub Total.discount Price Number: 7
* Sub URL Precision: 0.9231
* Sub URL Recall: 0.9231
* Sub URL F1: 0.9231
* Sub URL Number: 13
* Sub Total.service Price Precision: 1.0
* Sub Total.service Price Recall: 1.0
* Sub Total.service Price F1: 1.0
* Sub Total.service Price Number: 12
* Sub Total.subtotal Price Precision: 0.9714
* Sub Total.subtotal Price Recall: 0.9855
* Sub Total.subtotal Price F1: 0.9784
* Sub Total.subtotal Price Number: 69
* Sub URL Price Precision: 1.0
* Sub URL Price Recall: 1.0
* Sub URL Price F1: 1.0
* Sub URL Price Number: 47
* Total.cashprice Precision: 1.0
* Total.cashprice Recall: 0.9167
* Total.cashprice F1: 0.9565
* Total.cashprice Number: 72
* Total.changeprice Precision: 0.9672
* Total.changeprice Recall: 1.0
* Total.changeprice F1: 0.9833
* Total.changeprice Number: 59
* Total.creditcardprice Precision: 1.0
* Total.creditcardprice Recall: 0.9412
* Total.creditcardprice F1: 0.9697
* Total.creditcardprice Number: 17
* Total.emoneyprice Precision: 0.1667
* Total.emoneyprice Recall: 0.5
* Total.emoneyprice F1: 0.25
* Total.emoneyprice Number: 2
* Total.menuqty Cnt Precision: 0.9667
* Total.menuqty Cnt Recall: 1.0
* Total.menuqty Cnt F1: 0.9831
* Total.menuqty Cnt Number: 29
* Total.menutype Cnt Precision: 1.0
* Total.menutype Cnt Recall: 0.7143
* Total.menutype Cnt F1: 0.8333
* Total.menutype Cnt Number: 7
* URL Etc Precision: 0.0
* URL Etc Recall: 0.0
* URL Etc F1: 0.0
* URL Etc Number: 4
* URL Price Precision: 0.9709
* URL Price Recall: 0.9901
* URL Price F1: 0.9804
* URL Price Number: 101
* Overall Precision: 0.9627
* Overall Recall: 0.9671
* Overall F1: 0.9649
* Overall Accuracy: 0.9690


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 3000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.10.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 3000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.10.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #dataset-cord-layoutlmv3 #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 3000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.10.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #layoutlmv2 #token-classification #generated_from_trainer #dataset-cord-layoutlmv3 #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.1
* training\_steps: 3000
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.10.0+cu111
* Datasets 2.4.0
* Tokenizers 0.12.1