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# layoutlmv2-cord-ner

This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0952
- Precision: 0.9639
- Recall: 0.9741
- F1: 0.9690
- Accuracy: 0.9911

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 113  | 0.5962          | 0.8714    | 0.8973 | 0.8842 | 0.9405   |
| No log        | 2.0   | 226  | 0.4064          | 0.8713    | 0.9098 | 0.8901 | 0.9511   |
| No log        | 3.0   | 339  | 0.2687          | 0.9314    | 0.9386 | 0.9350 | 0.9754   |
| No log        | 4.0   | 452  | 0.2007          | 0.9355    | 0.9472 | 0.9413 | 0.9792   |
| 0.4677        | 5.0   | 565  | 0.1625          | 0.9497    | 0.9597 | 0.9547 | 0.9834   |
| 0.4677        | 6.0   | 678  | 0.1326          | 0.9526    | 0.9645 | 0.9585 | 0.9868   |
| 0.4677        | 7.0   | 791  | 0.1212          | 0.9508    | 0.9645 | 0.9576 | 0.9851   |
| 0.4677        | 8.0   | 904  | 0.1019          | 0.9675    | 0.9712 | 0.9693 | 0.9911   |
| 0.1131        | 9.0   | 1017 | 0.1029          | 0.9545    | 0.9664 | 0.9604 | 0.9881   |
| 0.1131        | 10.0  | 1130 | 0.0952          | 0.9639    | 0.9741 | 0.9690 | 0.9911   |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.9.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv2-cord-ner", "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 

layoutlmv2-cord-ner
===================


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


* Loss: 0.0952
* Precision: 0.9639
* Recall: 0.9741
* F1: 0.9690
* Accuracy: 0.9911


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
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6



### 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
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 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
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6
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: 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
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.9.0+cu111
* Datasets 1.18.4
* Tokenizers 0.11.6