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# lmv2-g-recp-992-doc-09-09

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: 0.2241
- Purchase Time Precision: 0.872
- Purchase Time Recall: 0.8516
- Purchase Time F1: 0.8617
- Purchase Time Number: 128
- Receipt Date Precision: 0.8713
- Receipt Date Recall: 0.8817
- Receipt Date F1: 0.8765
- Receipt Date Number: 169
- Sub Total Precision: 0.8211
- Sub Total Recall: 0.7091
- Sub Total F1: 0.7610
- Sub Total Number: 110
- Supplier Address Precision: 0.7009
- Supplier Address Recall: 0.7193
- Supplier Address F1: 0.7100
- Supplier Address Number: 114
- Supplier Name Precision: 0.7442
- Supplier Name Recall: 0.7191
- Supplier Name F1: 0.7314
- Supplier Name Number: 267
- Tip Amount Precision: 0.6667
- Tip Amount Recall: 1.0
- Tip Amount F1: 0.8
- Tip Amount Number: 2
- Total Precision: 0.8436
- Total Recall: 0.8251
- Total F1: 0.8343
- Total Number: 183
- Total Tax Amount Precision: 0.8361
- Total Tax Amount Recall: 0.7846
- Total Tax Amount F1: 0.8095
- Total Tax Amount Number: 65
- Overall Precision: 0.8067
- Overall Recall: 0.7842
- Overall F1: 0.7953
- Overall Accuracy: 0.9728

## 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 | Purchase Time Precision | Purchase Time Recall | Purchase Time F1 | Purchase Time Number | Receipt Date Precision | Receipt Date Recall | Receipt Date F1 | Receipt Date Number | Sub Total Precision | Sub Total Recall | Sub Total F1 | Sub Total Number | Supplier Address Precision | Supplier Address Recall | Supplier Address F1 | Supplier Address Number | Supplier Name Precision | Supplier Name Recall | Supplier Name F1 | Supplier Name Number | Tip Amount Precision | Tip Amount Recall | Tip Amount F1 | Tip Amount Number | Total Precision | Total Recall | Total F1 | Total Number | Total Tax Amount Precision | Total Tax Amount Recall | Total Tax Amount F1 | Total Tax Amount Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:-------------------:|:----------------:|:------------:|:----------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:---------------:|:------------:|:--------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.9017        | 1.0   | 793   | 0.3748          | 0.0                     | 0.0                  | 0.0              | 128                  | 0.5                    | 0.0710              | 0.1244          | 169                 | 0.0                 | 0.0              | 0.0          | 110              | 0.4632                     | 0.5526                  | 0.504               | 114                     | 0.3724                  | 0.2022               | 0.2621           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.7387          | 0.4481       | 0.5578   | 183          | 0.0                        | 0.0                     | 0.0                 | 65                      | 0.4637            | 0.2033         | 0.2827     | 0.9330           |
| 0.2651        | 2.0   | 1586  | 0.2025          | 0.8                     | 0.8438               | 0.8213           | 128                  | 0.8274                 | 0.8225              | 0.8249          | 169                 | 0.4                 | 0.0182           | 0.0348       | 110              | 0.5329                     | 0.7105                  | 0.6090              | 114                     | 0.5886                  | 0.6592               | 0.6219           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.5720          | 0.8470       | 0.6828   | 183          | 1.0                        | 0.0308                  | 0.0597              | 65                      | 0.6424            | 0.6387         | 0.6406     | 0.9624           |
| 0.1403        | 3.0   | 2379  | 0.1585          | 0.8248                  | 0.8828               | 0.8528           | 128                  | 0.7897                 | 0.9112              | 0.8462          | 169                 | 0.7054              | 0.7182           | 0.7117       | 110              | 0.5931                     | 0.7544                  | 0.6641              | 114                     | 0.6288                  | 0.6217               | 0.6252           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.7877          | 0.7705       | 0.7790   | 183          | 0.8276                     | 0.7385                  | 0.7805              | 65                      | 0.7220            | 0.7582         | 0.7397     | 0.9683           |
| 0.0935        | 4.0   | 3172  | 0.1771          | 0.7891                  | 0.7891               | 0.7891           | 128                  | 0.6474                 | 0.7278              | 0.6852          | 169                 | 0.8205              | 0.5818           | 0.6809       | 110              | 0.6074                     | 0.7193                  | 0.6586              | 114                     | 0.6548                  | 0.6891               | 0.6715           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8476          | 0.7596       | 0.8012   | 183          | 0.75                       | 0.2308                  | 0.3529              | 65                      | 0.7108            | 0.6821         | 0.6962     | 0.9648           |
| 0.0684        | 5.0   | 3965  | 0.1552          | 0.9237                  | 0.8516               | 0.8862           | 128                  | 0.8362                 | 0.8757              | 0.8555          | 169                 | 0.7629              | 0.6727           | 0.7150       | 110              | 0.6029                     | 0.7193                  | 0.6560              | 114                     | 0.7167                  | 0.6442               | 0.6785           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8128          | 0.8306       | 0.8216   | 183          | 0.7937                     | 0.7692                  | 0.7813              | 65                      | 0.7731            | 0.7582         | 0.7656     | 0.9696           |
| 0.0491        | 6.0   | 4758  | 0.1702          | 0.8760                  | 0.8828               | 0.8794           | 128                  | 0.8352                 | 0.8698              | 0.8522          | 169                 | 0.8056              | 0.7909           | 0.7982       | 110              | 0.5894                     | 0.7807                  | 0.6717              | 114                     | 0.6844                  | 0.6742               | 0.6792           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8778          | 0.8634       | 0.8705   | 183          | 0.9074                     | 0.7538                  | 0.8235              | 65                      | 0.7757            | 0.7929         | 0.7842     | 0.9703           |
| 0.0472        | 7.0   | 5551  | 0.2037          | 0.8952                  | 0.8672               | 0.8810           | 128                  | 0.8876                 | 0.8876              | 0.8876          | 169                 | 0.8                 | 0.7273           | 0.7619       | 110              | 0.6557                     | 0.7018                  | 0.6780              | 114                     | 0.7953                  | 0.6404               | 0.7095           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8795          | 0.7978       | 0.8367   | 183          | 0.9394                     | 0.4769                  | 0.6327              | 65                      | 0.8278            | 0.7408         | 0.7819     | 0.9701           |
| 0.0361        | 8.0   | 6344  | 0.1862          | 0.875                   | 0.8203               | 0.8468           | 128                  | 0.7978                 | 0.8402              | 0.8184          | 169                 | 0.7739              | 0.8091           | 0.7911       | 110              | 0.6512                     | 0.7368                  | 0.6914              | 114                     | 0.6906                  | 0.6854               | 0.6880           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8486          | 0.8579       | 0.8533   | 183          | 0.6780                     | 0.6154                  | 0.6452              | 65                      | 0.7612            | 0.7707         | 0.7659     | 0.9701           |
| 0.0318        | 9.0   | 7137  | 0.1889          | 0.9                     | 0.8438               | 0.8710           | 128                  | 0.8743                 | 0.8639              | 0.8690          | 169                 | 0.875               | 0.6364           | 0.7368       | 110              | 0.6417                     | 0.6754                  | 0.6581              | 114                     | 0.6914                  | 0.6966               | 0.6940           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.7833          | 0.8689       | 0.8238   | 183          | 0.7797                     | 0.7077                  | 0.7419              | 65                      | 0.7772            | 0.7630         | 0.7701     | 0.9697           |
| 0.3481        | 10.0  | 7930  | 0.7581          | 0.0                     | 0.0                  | 0.0              | 128                  | 0.0                    | 0.0                 | 0.0             | 169                 | 0.0                 | 0.0              | 0.0          | 110              | 0.0                        | 0.0                     | 0.0                 | 114                     | 0.0                     | 0.0                  | 0.0              | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.0             | 0.0          | 0.0      | 183          | 0.0                        | 0.0                     | 0.0                 | 65                      | 0.0               | 0.0            | 0.0        | 0.8967           |
| 0.7157        | 11.0  | 8723  | 0.7634          | 0.0                     | 0.0                  | 0.0              | 128                  | 0.0                    | 0.0                 | 0.0             | 169                 | 0.0                 | 0.0              | 0.0          | 110              | 0.0                        | 0.0                     | 0.0                 | 114                     | 0.0                     | 0.0                  | 0.0              | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.0             | 0.0          | 0.0      | 183          | 0.0                        | 0.0                     | 0.0                 | 65                      | 0.0               | 0.0            | 0.0        | 0.8967           |
| 0.7136        | 12.0  | 9516  | 0.7611          | 0.0                     | 0.0                  | 0.0              | 128                  | 0.0                    | 0.0                 | 0.0             | 169                 | 0.0                 | 0.0              | 0.0          | 110              | 0.0                        | 0.0                     | 0.0                 | 114                     | 0.0                     | 0.0                  | 0.0              | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.0             | 0.0          | 0.0      | 183          | 0.0                        | 0.0                     | 0.0                 | 65                      | 0.0               | 0.0            | 0.0        | 0.8967           |
| 0.1095        | 13.0  | 10309 | 0.1744          | 0.8284                  | 0.8672               | 0.8473           | 128                  | 0.8531                 | 0.8935              | 0.8728          | 169                 | 0.7717              | 0.6455           | 0.7030       | 110              | 0.5662                     | 0.6754                  | 0.6160              | 114                     | 0.6424                  | 0.6929               | 0.6667           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8211          | 0.8525       | 0.8365   | 183          | 0.8214                     | 0.7077                  | 0.7603              | 65                      | 0.7428            | 0.7678         | 0.7551     | 0.9698           |
| 0.0316        | 14.0  | 11102 | 0.1812          | 0.8943                  | 0.8594               | 0.8765           | 128                  | 0.8409                 | 0.8757              | 0.8580          | 169                 | 0.8415              | 0.6273           | 0.7188       | 110              | 0.5714                     | 0.6667                  | 0.6154              | 114                     | 0.6279                  | 0.7079               | 0.6655           | 267                  | 1.0                  | 0.5               | 0.6667        | 2                 | 0.8256          | 0.8798       | 0.8519   | 183          | 0.8136                     | 0.7385                  | 0.7742              | 65                      | 0.7495            | 0.7726         | 0.7609     | 0.9703           |
| 0.0226        | 15.0  | 11895 | 0.2132          | 0.8843                  | 0.8359               | 0.8594           | 128                  | 0.8476                 | 0.8225              | 0.8348          | 169                 | 0.7525              | 0.6909           | 0.7204       | 110              | 0.5804                     | 0.7281                  | 0.6459              | 114                     | 0.6679                  | 0.6929               | 0.6801           | 267                  | 0.2                  | 0.5               | 0.2857        | 2                 | 0.8571          | 0.8525       | 0.8548   | 183          | 0.4835                     | 0.6769                  | 0.5641              | 65                      | 0.7297            | 0.7620         | 0.7455     | 0.9672           |
| 0.0241        | 16.0  | 12688 | 0.1962          | 0.8984                  | 0.8984               | 0.8984           | 128                  | 0.8613                 | 0.8817              | 0.8713          | 169                 | 0.6615              | 0.7818           | 0.7167       | 110              | 0.6                        | 0.7368                  | 0.6614              | 114                     | 0.6431                  | 0.7154               | 0.6773           | 267                  | 0.0833               | 0.5               | 0.1429        | 2                 | 0.8795          | 0.7978       | 0.8367   | 183          | 0.7727                     | 0.7846                  | 0.7786              | 65                      | 0.7401            | 0.7929         | 0.7656     | 0.9709           |
| 0.0155        | 17.0  | 13481 | 0.1995          | 0.8906                  | 0.8906               | 0.8906           | 128                  | 0.8678                 | 0.8935              | 0.8805          | 169                 | 0.7438              | 0.8182           | 0.7792       | 110              | 0.6042                     | 0.7632                  | 0.6744              | 114                     | 0.6193                  | 0.7678               | 0.6856           | 267                  | 1.0                  | 0.5               | 0.6667        | 2                 | 0.8325          | 0.8689       | 0.8503   | 183          | 0.8644                     | 0.7846                  | 0.8226              | 65                      | 0.7467            | 0.8266         | 0.7846     | 0.9696           |
| 0.0165        | 18.0  | 14274 | 0.2402          | 0.8966                  | 0.8125               | 0.8525           | 128                  | 0.8293                 | 0.8047              | 0.8168          | 169                 | 0.8118              | 0.6273           | 0.7077       | 110              | 0.5766                     | 0.6930                  | 0.6295              | 114                     | 0.7220                  | 0.6517               | 0.6850           | 267                  | 1.0                  | 1.0               | 1.0           | 2                 | 0.8603          | 0.8415       | 0.8508   | 183          | 0.7826                     | 0.5538                  | 0.6486              | 65                      | 0.7773            | 0.7264         | 0.7510     | 0.9683           |
| 0.0721        | 19.0  | 15067 | 0.2718          | 0.3506                  | 0.6328               | 0.4513           | 128                  | 0.7268                 | 0.7870              | 0.7557          | 169                 | 0.7742              | 0.4364           | 0.5581       | 110              | 0.5271                     | 0.5965                  | 0.5597              | 114                     | 0.5294                  | 0.5056               | 0.5172           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.7526          | 0.7978       | 0.7745   | 183          | 0.7414                     | 0.6615                  | 0.6992              | 65                      | 0.5881            | 0.6301         | 0.6084     | 0.9564           |
| 0.0136        | 20.0  | 15860 | 0.2213          | 0.8651                  | 0.8516               | 0.8583           | 128                  | 0.8555                 | 0.8757              | 0.8655          | 169                 | 0.8191              | 0.7              | 0.7549       | 110              | 0.6103                     | 0.7281                  | 0.664               | 114                     | 0.6977                  | 0.6742               | 0.6857           | 267                  | 1.0                  | 0.5               | 0.6667        | 2                 | 0.8571          | 0.8197       | 0.8380   | 183          | 0.7656                     | 0.7538                  | 0.7597              | 65                      | 0.7760            | 0.7678         | 0.7719     | 0.9697           |
| 0.0111        | 21.0  | 16653 | 0.2241          | 0.872                   | 0.8516               | 0.8617           | 128                  | 0.8713                 | 0.8817              | 0.8765          | 169                 | 0.8211              | 0.7091           | 0.7610       | 110              | 0.7009                     | 0.7193                  | 0.7100              | 114                     | 0.7442                  | 0.7191               | 0.7314           | 267                  | 0.6667               | 1.0               | 0.8           | 2                 | 0.8436          | 0.8251       | 0.8343   | 183          | 0.8361                     | 0.7846                  | 0.8095              | 65                      | 0.8067            | 0.7842         | 0.7953     | 0.9728           |
| 0.011         | 22.0  | 17446 | 0.2206          | 0.7770                  | 0.8984               | 0.8333           | 128                  | 0.8270                 | 0.9053              | 0.8644          | 169                 | 0.8586              | 0.7727           | 0.8134       | 110              | 0.5985                     | 0.6930                  | 0.6423              | 114                     | 0.6618                  | 0.6742               | 0.6679           | 267                  | 0.0                  | 0.0               | 0.0           | 2                 | 0.8870          | 0.8579       | 0.8722   | 183          | 0.7391                     | 0.7846                  | 0.7612              | 65                      | 0.7579            | 0.7900         | 0.7736     | 0.9697           |
| 0.0104        | 23.0  | 18239 | 0.2571          | 0.9310                  | 0.8438               | 0.8852           | 128                  | 0.875                  | 0.8698              | 0.8724          | 169                 | 0.8316              | 0.7182           | 0.7707       | 110              | 0.6417                     | 0.6754                  | 0.6581              | 114                     | 0.7386                  | 0.6667               | 0.7008           | 267                  | 0.1429               | 0.5               | 0.2222        | 2                 | 0.8579          | 0.8579       | 0.8579   | 183          | 0.7812                     | 0.7692                  | 0.7752              | 65                      | 0.8018            | 0.7678         | 0.7844     | 0.9705           |
| 0.0132        | 24.0  | 19032 | 0.2252          | 0.8810                  | 0.8672               | 0.8740           | 128                  | 0.8297                 | 0.8935              | 0.8604          | 169                 | 0.7607              | 0.8091           | 0.7841       | 110              | 0.6074                     | 0.7193                  | 0.6586              | 114                     | 0.6578                  | 0.7416               | 0.6972           | 267                  | 0.3333               | 1.0               | 0.5           | 2                 | 0.8659          | 0.8470       | 0.8564   | 183          | 0.7966                     | 0.7231                  | 0.7581              | 65                      | 0.7557            | 0.8044         | 0.7793     | 0.9717           |
| 0.0114        | 25.0  | 19825 | 0.2303          | 0.8917                  | 0.8359               | 0.8629           | 128                  | 0.8947                 | 0.9053              | 0.9000          | 169                 | 0.8144              | 0.7182           | 0.7633       | 110              | 0.6296                     | 0.7456                  | 0.6827              | 114                     | 0.6937                  | 0.7041               | 0.6989           | 267                  | 1.0                  | 0.5               | 0.6667        | 2                 | 0.8533          | 0.8579       | 0.8556   | 183          | 0.8913                     | 0.6308                  | 0.7387              | 65                      | 0.7912            | 0.7813         | 0.7862     | 0.9705           |
| 0.0121        | 26.0  | 20618 | 0.2485          | 0.8810                  | 0.8672               | 0.8740           | 128                  | 0.8793                 | 0.9053              | 0.8921          | 169                 | 0.8667              | 0.7091           | 0.7800       | 110              | 0.5926                     | 0.7018                  | 0.6426              | 114                     | 0.7446                  | 0.6442               | 0.6908           | 267                  | 0.25                 | 0.5               | 0.3333        | 2                 | 0.8361          | 0.8361       | 0.8361   | 183          | 0.7581                     | 0.7231                  | 0.7402              | 65                      | 0.7910            | 0.7659         | 0.7783     | 0.9705           |
| 0.0124        | 27.0  | 21411 | 0.2280          | 0.8504                  | 0.8438               | 0.8471           | 128                  | 0.8391                 | 0.8639              | 0.8513          | 169                 | 0.8119              | 0.7455           | 0.7773       | 110              | 0.6435                     | 0.6491                  | 0.6463              | 114                     | 0.6259                  | 0.6891               | 0.6560           | 267                  | 0.4                  | 1.0               | 0.5714        | 2                 | 0.8548          | 0.8689       | 0.8618   | 183          | 0.8627                     | 0.6769                  | 0.7586              | 65                      | 0.7588            | 0.7697         | 0.7642     | 0.9702           |
| 0.0111        | 28.0  | 22204 | 0.2728          | 0.8917                  | 0.8359               | 0.8629           | 128                  | 0.8704                 | 0.8343              | 0.8520          | 169                 | 0.9059              | 0.7              | 0.7897       | 110              | 0.5833                     | 0.6754                  | 0.6260              | 114                     | 0.6618                  | 0.6816               | 0.6716           | 267                  | 1.0                  | 0.5               | 0.6667        | 2                 | 0.8713          | 0.8142       | 0.8418   | 183          | 0.8837                     | 0.5846                  | 0.7037              | 65                      | 0.7806            | 0.7437         | 0.7617     | 0.9692           |
| 0.0079        | 29.0  | 22997 | 0.2596          | 0.8661                  | 0.8594               | 0.8627           | 128                  | 0.8817                 | 0.8817              | 0.8817          | 169                 | 0.7436              | 0.7909           | 0.7665       | 110              | 0.616                      | 0.6754                  | 0.6444              | 114                     | 0.6794                  | 0.6667               | 0.6730           | 267                  | 1.0                  | 1.0               | 1.0           | 2                 | 0.8681          | 0.8634       | 0.8658   | 183          | 0.8727                     | 0.7385                  | 0.8                 | 65                      | 0.7786            | 0.7794         | 0.7790     | 0.9705           |
| 0.0076        | 30.0  | 23790 | 0.2476          | 0.8088                  | 0.8594               | 0.8333           | 128                  | 0.8889                 | 0.8994              | 0.8941          | 169                 | 0.7909              | 0.7909           | 0.7909       | 110              | 0.6397                     | 0.7632                  | 0.6960              | 114                     | 0.6727                  | 0.6929               | 0.6827           | 267                  | 0.3333               | 1.0               | 0.5           | 2                 | 0.8641          | 0.8689       | 0.8665   | 183          | 0.6512                     | 0.8615                  | 0.7417              | 65                      | 0.7591            | 0.8073         | 0.7824     | 0.9705           |


### 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-recp-992-doc-09-09", "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-recp-992-doc-09-09
=========================


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: 0.2241
* Purchase Time Precision: 0.872
* Purchase Time Recall: 0.8516
* Purchase Time F1: 0.8617
* Purchase Time Number: 128
* Receipt Date Precision: 0.8713
* Receipt Date Recall: 0.8817
* Receipt Date F1: 0.8765
* Receipt Date Number: 169
* Sub Total Precision: 0.8211
* Sub Total Recall: 0.7091
* Sub Total F1: 0.7610
* Sub Total Number: 110
* Supplier Address Precision: 0.7009
* Supplier Address Recall: 0.7193
* Supplier Address F1: 0.7100
* Supplier Address Number: 114
* Supplier Name Precision: 0.7442
* Supplier Name Recall: 0.7191
* Supplier Name F1: 0.7314
* Supplier Name Number: 267
* Tip Amount Precision: 0.6667
* Tip Amount Recall: 1.0
* Tip Amount F1: 0.8
* Tip Amount Number: 2
* Total Precision: 0.8436
* Total Recall: 0.8251
* Total F1: 0.8343
* Total Number: 183
* Total Tax Amount Precision: 0.8361
* Total Tax Amount Recall: 0.7846
* Total Tax Amount F1: 0.8095
* Total Tax Amount Number: 65
* Overall Precision: 0.8067
* Overall Recall: 0.7842
* Overall F1: 0.7953
* Overall Accuracy: 0.9728


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