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# layoutlmv3-finetuned-registros_v3

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_registros_layoutv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1730
- Precision: 0.8168
- Recall: 0.8803
- F1: 0.8474
- Accuracy: 0.9726

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 10.87 | 250  | 0.4505          | 0.2272    | 0.2460 | 0.2362 | 0.8929   |
| 0.641         | 21.74 | 500  | 0.2718          | 0.6121    | 0.6715 | 0.6404 | 0.9374   |
| 0.641         | 32.61 | 750  | 0.1971          | 0.7854    | 0.8528 | 0.8177 | 0.9669   |
| 0.2206        | 43.48 | 1000 | 0.1730          | 0.8168    | 0.8803 | 0.8474 | 0.9726   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["data_registros_layoutv3"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-finetuned-registros_v3", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "data_registros_layoutv3", "type": "data_registros_layoutv3", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "precision", "value": 0.8168168168168168, "name": "Precision"}, {"type": "recall", "value": 0.8802588996763754, "name": "Recall"}, {"type": "f1", "value": 0.8473520249221185, "name": "F1"}, {"type": "accuracy", "value": 0.9726255293405929, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:data_registros_layoutv3 license:cc-by-nc-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-data_registros_layoutv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-finetuned-registros\_v3
==================================


This model is a fine-tuned version of microsoft/layoutlmv3-base on the data\_registros\_layoutv3 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1730
* Precision: 0.8168
* Recall: 0.8803
* F1: 0.8474
* Accuracy: 0.9726


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-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-data_registros_layoutv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-06
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 1000 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3