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# layoutlmv3-finetuned-cedulas_v3

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_cedulas_layoutv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0832
- Precision: 0.8992
- Recall: 0.9068
- F1: 0.9030
- 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: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 3.12  | 250  | 0.7409          | 0.2850    | 0.2729 | 0.2788 | 0.8614   |
| 0.9048        | 6.25  | 500  | 0.3660          | 0.6222    | 0.6559 | 0.6386 | 0.9393   |
| 0.9048        | 9.38  | 750  | 0.2132          | 0.7492    | 0.7593 | 0.7542 | 0.9544   |
| 0.2923        | 12.5  | 1000 | 0.1467          | 0.7830    | 0.7949 | 0.7889 | 0.9661   |
| 0.2923        | 15.62 | 1250 | 0.1172          | 0.8114    | 0.8237 | 0.8175 | 0.9701   |
| 0.1445        | 18.75 | 1500 | 0.1013          | 0.8560    | 0.8763 | 0.8660 | 0.9766   |
| 0.1445        | 21.88 | 1750 | 0.0952          | 0.8811    | 0.8915 | 0.8863 | 0.9794   |
| 0.0956        | 25.0  | 2000 | 0.0876          | 0.8923    | 0.8983 | 0.8953 | 0.9807   |
| 0.0956        | 28.12 | 2250 | 0.0840          | 0.9005    | 0.9051 | 0.9028 | 0.9811   |
| 0.0766        | 31.25 | 2500 | 0.0832          | 0.8992    | 0.9068 | 0.9030 | 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_cedulas_layoutv3"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-finetuned-cedulas_v3", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "data_cedulas_layoutv3", "type": "data_cedulas_layoutv3", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "precision", "value": 0.8991596638655462, "name": "Precision"}, {"type": "recall", "value": 0.9067796610169492, "name": "Recall"}, {"type": "f1", "value": 0.9029535864978903, "name": "F1"}, {"type": "accuracy", "value": 0.9816565809379728, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:data_cedulas_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_cedulas_layoutv3 #license-cc-by-nc-sa-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-finetuned-cedulas\_v3
================================


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


* Loss: 0.0832
* Precision: 0.8992
* Recall: 0.9068
* F1: 0.9030
* 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: 2500


### 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: 2500 ### 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_cedulas_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: 2500 ### Training results ### Framework versions


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