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# layoutlmv3-finetuned-registros_v2

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: 0.1473
- Precision: 0.8606
- Recall: 0.9374
- F1: 0.8974
- Accuracy: 0.9817

## 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  | 0.4204          | 0.4257    | 0.4351 | 0.4303 | 0.9104   |
| 0.6077        | 21.74 | 500  | 0.2246          | 0.7957    | 0.8654 | 0.8291 | 0.9683   |
| 0.6077        | 32.61 | 750  | 0.1636          | 0.8438    | 0.9218 | 0.8811 | 0.9765   |
| 0.1638        | 43.48 | 1000 | 0.1473          | 0.8606    | 0.9374 | 0.8974 | 0.9817   |


### 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_v2", "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": 0.860632183908046, "name": "Precision"}, {"type": "recall", "value": 0.9374021909233177, "name": "Recall"}, {"type": "f1", "value": 0.8973782771535581, "name": "F1"}, {"type": "accuracy", "value": 0.9816688664026983, "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\_v2
==================================


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: 0.1473
* Precision: 0.8606
* Recall: 0.9374
* F1: 0.8974
* Accuracy: 0.9817


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