
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# layoutlmv3-cord-ner

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1215
- Precision: 0.9448
- Recall: 0.9520
- F1: 0.9484
- Accuracy: 0.9762

## 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  | 0.1771          | 0.8485    | 0.8925 | 0.8700 | 0.9393   |
| No log        | 2.0   | 226  | 0.1584          | 0.8915    | 0.9146 | 0.9029 | 0.9524   |
| No log        | 3.0   | 339  | 0.1153          | 0.9160    | 0.9309 | 0.9234 | 0.9686   |
| No log        | 4.0   | 452  | 0.1477          | 0.9110    | 0.9136 | 0.9123 | 0.9592   |
| 0.1562        | 5.0   | 565  | 0.0861          | 0.9363    | 0.9443 | 0.9403 | 0.9741   |
| 0.1562        | 6.0   | 678  | 0.1165          | 0.9109    | 0.9415 | 0.9259 | 0.9673   |
| 0.1562        | 7.0   | 791  | 0.1280          | 0.9278    | 0.9367 | 0.9322 | 0.9707   |
| 0.1562        | 8.0   | 904  | 0.1122          | 0.9462    | 0.9453 | 0.9458 | 0.9762   |
| 0.0224        | 9.0   | 1017 | 0.1265          | 0.9431    | 0.9539 | 0.9485 | 0.9771   |
| 0.0224        | 10.0  | 1130 | 0.1215          | 0.9448    | 0.9520 | 0.9484 | 0.9762   |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-cord-ner", "results": []}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-cord-ner
===================


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


* Loss: 0.1215
* Precision: 0.9448
* Recall: 0.9520
* F1: 0.9484
* Accuracy: 0.9762


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 4.20.0.dev0
* Pytorch 1.11.0
* Datasets 2.1.0
* 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
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #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 4.20.0.dev0
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #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 4.20.0.dev0
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1