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# lmv2-g-pan-143doc-06-12

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: 0.0443
- Dob Precision: 1.0
- Dob Recall: 1.0
- Dob F1: 1.0
- Dob Number: 27
- Fname Precision: 1.0
- Fname Recall: 0.9643
- Fname F1: 0.9818
- Fname Number: 28
- Name Precision: 0.9630
- Name Recall: 0.9630
- Name F1: 0.9630
- Name Number: 27
- Pan Precision: 1.0
- Pan Recall: 1.0
- Pan F1: 1.0
- Pan Number: 26
- Overall Precision: 0.9907
- Overall Recall: 0.9815
- Overall F1: 0.9860
- Overall Accuracy: 0.9978

## 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 | Dob Precision | Dob Recall | Dob F1 | Dob Number | Fname Precision | Fname Recall | Fname F1 | Fname Number | Name Precision | Name Recall | Name F1 | Name Number | Pan Precision | Pan Recall | Pan F1 | Pan Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:---------------:|:------------:|:--------:|:------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 1.274         | 1.0   | 114  | 0.9098          | 0.9310        | 1.0        | 0.9643 | 27         | 0.1481          | 0.1429       | 0.1455   | 28           | 0.1639         | 0.3704      | 0.2273  | 27          | 0.8125        | 1.0        | 0.8966 | 26         | 0.4497            | 0.6204         | 0.5214     | 0.9143           |
| 0.7133        | 2.0   | 228  | 0.5771          | 0.9310        | 1.0        | 0.9643 | 27         | 0.2093          | 0.3214       | 0.2535   | 28           | 0.6562         | 0.7778      | 0.7119  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.6336            | 0.7685         | 0.6946     | 0.9443           |
| 0.4593        | 3.0   | 342  | 0.4018          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8276          | 0.8571       | 0.8421   | 28           | 0.9259         | 0.9259      | 0.9259  | 27          | 1.0           | 1.0        | 1.0    | 26         | 0.9273            | 0.9444         | 0.9358     | 0.9655           |
| 0.3011        | 4.0   | 456  | 0.2638          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.9286       | 0.9630   | 28           | 0.9259         | 0.9259      | 0.9259  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9630            | 0.9630         | 0.9630     | 0.9811           |
| 0.2209        | 5.0   | 570  | 0.2108          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8621          | 0.8929       | 0.8772   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9204            | 0.9630         | 0.9412     | 0.9811           |
| 0.1724        | 6.0   | 684  | 0.1671          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9286          | 0.9286       | 0.9286   | 28           | 0.8667         | 0.9630      | 0.9123  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9130            | 0.9722         | 0.9417     | 0.9844           |
| 0.1285        | 7.0   | 798  | 0.1754          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8929          | 0.8929       | 0.8929   | 28           | 0.9630         | 0.9630      | 0.9630  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9455            | 0.9630         | 0.9541     | 0.9788           |
| 0.0999        | 8.0   | 912  | 0.1642          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9615          | 0.8929       | 0.9259   | 28           | 0.9630         | 0.9630      | 0.9630  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9630            | 0.9630         | 0.9630     | 0.9811           |
| 0.0862        | 9.0   | 1026 | 0.1417          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.8966         | 0.9630      | 0.9286  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9292            | 0.9722         | 0.9502     | 0.9788           |
| 0.0722        | 10.0  | 1140 | 0.1317          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9630          | 0.9286       | 0.9455   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9545            | 0.9722         | 0.9633     | 0.9822           |
| 0.0748        | 11.0  | 1254 | 0.1220          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.8929       | 0.9434   | 28           | 1.0            | 0.9630      | 0.9811  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9720            | 0.9630         | 0.9674     | 0.9833           |
| 0.0549        | 12.0  | 1368 | 0.1157          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.8667         | 0.9630      | 0.9123  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9052            | 0.9722         | 0.9375     | 0.9811           |
| 0.0444        | 13.0  | 1482 | 0.1198          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.8929       | 0.9434   | 28           | 0.9630         | 0.9630      | 0.9630  | 27          | 0.9630        | 1.0        | 0.9811 | 26         | 0.9720            | 0.9630         | 0.9674     | 0.9811           |
| 0.0371        | 14.0  | 1596 | 0.1082          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.8966         | 0.9630      | 0.9286  | 27          | 0.7879        | 1.0        | 0.8814 | 26         | 0.8824            | 0.9722         | 0.9251     | 0.9833           |
| 0.036         | 15.0  | 1710 | 0.1257          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9630          | 0.9286       | 0.9455   | 28           | 0.9630         | 0.9630      | 0.9630  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9459            | 0.9722         | 0.9589     | 0.9800           |
| 0.0291        | 16.0  | 1824 | 0.0930          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9643          | 0.9643       | 0.9643   | 28           | 0.9643         | 1.0         | 0.9818  | 27          | 0.8667        | 1.0        | 0.9286 | 26         | 0.9386            | 0.9907         | 0.9640     | 0.9900           |
| 0.0267        | 17.0  | 1938 | 0.0993          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9286          | 0.9286       | 0.9286   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9375            | 0.9722         | 0.9545     | 0.9844           |
| 0.023         | 18.0  | 2052 | 0.1240          | 0.9643        | 1.0        | 0.9818 | 27         | 0.7941          | 0.9643       | 0.8710   | 28           | 0.9643         | 1.0         | 0.9818  | 27          | 0.8387        | 1.0        | 0.9123 | 26         | 0.8843            | 0.9907         | 0.9345     | 0.9800           |
| 0.0379        | 19.0  | 2166 | 0.1154          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.9286       | 0.9630   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9545            | 0.9722         | 0.9633     | 0.9833           |
| 0.0199        | 20.0  | 2280 | 0.1143          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.9286       | 0.9630   | 28           | 0.8966         | 0.9630      | 0.9286  | 27          | 0.8667        | 1.0        | 0.9286 | 26         | 0.9292            | 0.9722         | 0.9502     | 0.9844           |
| 0.0256        | 21.0  | 2394 | 0.1175          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8667          | 0.9286       | 0.8966   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9211            | 0.9722         | 0.9459     | 0.9811           |
| 0.0388        | 22.0  | 2508 | 0.0964          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.9310         | 1.0         | 0.9643  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9217            | 0.9815         | 0.9507     | 0.9855           |
| 0.0334        | 23.0  | 2622 | 0.1186          | 0.9643        | 1.0        | 0.9818 | 27         | 1.0             | 0.9286       | 0.9630   | 28           | 1.0            | 0.9630      | 0.9811  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9633            | 0.9722         | 0.9677     | 0.9833           |
| 0.0134        | 24.0  | 2736 | 0.1193          | 0.9643        | 1.0        | 0.9818 | 27         | 0.9630          | 0.9286       | 0.9455   | 28           | 1.0            | 0.9630      | 0.9811  | 27          | 0.9286        | 1.0        | 0.9630 | 26         | 0.9633            | 0.9722         | 0.9677     | 0.9822           |
| 0.0157        | 25.0  | 2850 | 0.1078          | 1.0           | 1.0        | 1.0    | 27         | 0.9259          | 0.8929       | 0.9091   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9369            | 0.9630         | 0.9498     | 0.9833           |
| 0.0157        | 26.0  | 2964 | 0.0758          | 1.0           | 1.0        | 1.0    | 27         | 0.8929          | 0.8929       | 0.8929   | 28           | 1.0            | 1.0         | 1.0     | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9459            | 0.9722         | 0.9589     | 0.9911           |
| 0.0096        | 27.0  | 3078 | 0.0766          | 1.0           | 1.0        | 1.0    | 27         | 0.8929          | 0.8929       | 0.8929   | 28           | 1.0            | 1.0         | 1.0     | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9459            | 0.9722         | 0.9589     | 0.9889           |
| 0.0135        | 28.0  | 3192 | 0.0443          | 1.0           | 1.0        | 1.0    | 27         | 1.0             | 0.9643       | 0.9818   | 28           | 0.9630         | 0.9630      | 0.9630  | 27          | 1.0           | 1.0        | 1.0    | 26         | 0.9907            | 0.9815         | 0.9860     | 0.9978           |
| 0.012         | 29.0  | 3306 | 0.1153          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.8667         | 0.9630      | 0.9123  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9052            | 0.9722         | 0.9375     | 0.9822           |
| 0.0069        | 30.0  | 3420 | 0.1373          | 0.9643        | 1.0        | 0.9818 | 27         | 0.8966          | 0.9286       | 0.9123   | 28           | 0.9286         | 0.9630      | 0.9455  | 27          | 0.8966        | 1.0        | 0.9455 | 26         | 0.9211            | 0.9722         | 0.9459     | 0.9777           |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0+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-pan-143doc-06-12", "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-pan-143doc-06-12
=======================


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: 0.0443
* Dob Precision: 1.0
* Dob Recall: 1.0
* Dob F1: 1.0
* Dob Number: 27
* Fname Precision: 1.0
* Fname Recall: 0.9643
* Fname F1: 0.9818
* Fname Number: 28
* Name Precision: 0.9630
* Name Recall: 0.9630
* Name F1: 0.9630
* Name Number: 27
* Pan Precision: 1.0
* Pan Recall: 1.0
* Pan F1: 1.0
* Pan Number: 26
* Overall Precision: 0.9907
* Overall Recall: 0.9815
* Overall F1: 0.9860
* Overall Accuracy: 0.9978


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 4.20.0.dev0
* Pytorch 1.11.0+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 4.20.0.dev0
* Pytorch 1.11.0+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 4.20.0.dev0
* Pytorch 1.11.0+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 4.20.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1