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# lmv2ubiai-pan8doc-06-11

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: 0.9633
- Dob Precision: 1.0
- Dob Recall: 1.0
- Dob F1: 1.0
- Dob Number: 2
- Fname Precision: 0.6667
- Fname Recall: 1.0
- Fname F1: 0.8
- Fname Number: 2
- Name Precision: 1.0
- Name Recall: 1.0
- Name F1: 1.0
- Name Number: 2
- Pan Precision: 1.0
- Pan Recall: 1.0
- Pan F1: 1.0
- Pan Number: 2
- Overall Precision: 0.8889
- Overall Recall: 1.0
- Overall F1: 0.9412
- Overall Accuracy: 0.9821

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:---------------:|:------------:|:--------:|:------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 2.1195        | 1.0   | 6    | 1.7519          | 0.0           | 0.0        | 0.0    | 2          | 0.0             | 0.0          | 0.0      | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.0               | 0.0            | 0.0        | 0.7857           |
| 1.6994        | 2.0   | 12   | 1.5117          | 0.0           | 0.0        | 0.0    | 2          | 0.0             | 0.0          | 0.0      | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.0               | 0.0            | 0.0        | 0.7857           |
| 1.5521        | 3.0   | 18   | 1.4130          | 0.0           | 0.0        | 0.0    | 2          | 0.0             | 0.0          | 0.0      | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.0               | 0.0            | 0.0        | 0.7857           |
| 1.4726        | 4.0   | 24   | 1.3410          | 0.0           | 0.0        | 0.0    | 2          | 0.0             | 0.0          | 0.0      | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.0               | 0.0            | 0.0        | 0.7857           |
| 1.395         | 5.0   | 30   | 1.2693          | 0.0           | 0.0        | 0.0    | 2          | 0.0             | 0.0          | 0.0      | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.0               | 0.0            | 0.0        | 0.7857           |
| 1.3131        | 6.0   | 36   | 1.2079          | 1.0           | 1.0        | 1.0    | 2          | 0.1667          | 0.5          | 0.25     | 2            | 0.0            | 0.0         | 0.0     | 2           | 0.0           | 0.0        | 0.0    | 2          | 0.3               | 0.375          | 0.3333     | 0.8929           |
| 1.2474        | 7.0   | 42   | 1.1495          | 1.0           | 1.0        | 1.0    | 2          | 0.2             | 0.5          | 0.2857   | 2            | 0.0            | 0.0         | 0.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.4167            | 0.625          | 0.5        | 0.9286           |
| 1.1869        | 8.0   | 48   | 1.0942          | 1.0           | 1.0        | 1.0    | 2          | 0.2             | 0.5          | 0.2857   | 2            | 0.0            | 0.0         | 0.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.4167            | 0.625          | 0.5        | 0.9286           |
| 1.1369        | 9.0   | 54   | 1.0453          | 1.0           | 1.0        | 1.0    | 2          | 0.4             | 1.0          | 0.5714   | 2            | 0.0            | 0.0         | 0.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.5455            | 0.75           | 0.6316     | 0.9464           |
| 1.0882        | 10.0  | 60   | 1.0054          | 1.0           | 1.0        | 1.0    | 2          | 0.5             | 1.0          | 0.6667   | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.7               | 0.875          | 0.7778     | 0.9643           |
| 1.0482        | 11.0  | 66   | 0.9633          | 1.0           | 1.0        | 1.0    | 2          | 0.6667          | 1.0          | 0.8      | 2            | 1.0            | 1.0         | 1.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.8889            | 1.0            | 0.9412     | 0.9821           |
| 1.017         | 12.0  | 72   | 0.9368          | 1.0           | 1.0        | 1.0    | 2          | 0.6667          | 1.0          | 0.8      | 2            | 1.0            | 1.0         | 1.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.8889            | 1.0            | 0.9412     | 0.9643           |
| 0.9825        | 13.0  | 78   | 0.9139          | 1.0           | 1.0        | 1.0    | 2          | 0.6667          | 1.0          | 0.8      | 2            | 1.0            | 1.0         | 1.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.8889            | 1.0            | 0.9412     | 0.9821           |
| 0.9459        | 14.0  | 84   | 0.8837          | 1.0           | 1.0        | 1.0    | 2          | 0.6667          | 1.0          | 0.8      | 2            | 1.0            | 1.0         | 1.0     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.8889            | 1.0            | 0.9412     | 0.9643           |
| 0.9155        | 15.0  | 90   | 0.8472          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.8819        | 16.0  | 96   | 0.8231          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.8523        | 17.0  | 102  | 0.7957          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.6667         | 1.0         | 0.8     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.8889            | 1.0            | 0.9412     | 0.9821           |
| 0.8251        | 18.0  | 108  | 0.7681          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.7982        | 19.0  | 114  | 0.7533          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.7762        | 20.0  | 120  | 0.7283          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.7558        | 21.0  | 126  | 0.7114          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.7346        | 22.0  | 132  | 0.6889          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.7116        | 23.0  | 138  | 0.6697          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.6898        | 24.0  | 144  | 0.6593          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.6748        | 25.0  | 150  | 0.6356          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.6487        | 26.0  | 156  | 0.6142          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.6312        | 27.0  | 162  | 0.6008          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.6156        | 28.0  | 168  | 0.5855          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.5961        | 29.0  | 174  | 0.5625          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |
| 0.5781        | 30.0  | 180  | 0.5553          | 1.0           | 1.0        | 1.0    | 2          | 1.0             | 1.0          | 1.0      | 2            | 0.5            | 0.5         | 0.5     | 2           | 1.0           | 1.0        | 1.0    | 2          | 0.875             | 0.875          | 0.875      | 0.9643           |


### 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": "lmv2ubiai-pan8doc-06-11", "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 

lmv2ubiai-pan8doc-06-11
=======================


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: 0.9633
* Dob Precision: 1.0
* Dob Recall: 1.0
* Dob F1: 1.0
* Dob Number: 2
* Fname Precision: 0.6667
* Fname Recall: 1.0
* Fname F1: 0.8
* Fname Number: 2
* Name Precision: 1.0
* Name Recall: 1.0
* Name F1: 1.0
* Name Number: 2
* Pan Precision: 1.0
* Pan Recall: 1.0
* Pan F1: 1.0
* Pan Number: 2
* Overall Precision: 0.8889
* Overall Recall: 1.0
* Overall F1: 0.9412
* Overall Accuracy: 0.9821


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