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# layoutlmv3-finetuned-registros_100

This model was trained from scratch on the data_registros_layoutv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0050
- Precision: 0.9968
- Recall: 0.9951
- F1: 0.9960
- Accuracy: 0.9995

## 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: 600

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 4.35  | 100  | 0.0106          | 0.9871    | 0.9935 | 0.9903 | 0.9991   |
| No log        | 8.7   | 200  | 0.0073          | 0.9984    | 0.9968 | 0.9976 | 0.9997   |
| No log        | 13.04 | 300  | 0.0061          | 0.9968    | 0.9968 | 0.9968 | 0.9997   |
| No log        | 17.39 | 400  | 0.0048          | 0.9968    | 0.9984 | 0.9976 | 0.9997   |
| 0.0109        | 21.74 | 500  | 0.0053          | 0.9968    | 0.9968 | 0.9968 | 0.9997   |
| 0.0109        | 26.09 | 600  | 0.0050          | 0.9968    | 0.9951 | 0.9960 | 0.9995   |


### Framework versions

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

{"tags": ["generated_from_trainer"], "datasets": ["data_registros_layoutv3"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "layoutlmv3-finetuned-registros_100", "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": 0.9967585089141004, "name": "Precision"}, {"type": "recall", "value": 0.9951456310679612, "name": "Recall"}, {"type": "f1", "value": 0.9959514170040485, "name": "F1"}, {"type": "accuracy", "value": 0.999531542785759, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard layoutlmv3 token-classification generated_from_trainer dataset:data_registros_layoutv3 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #layoutlmv3 #token-classification #generated_from_trainer #dataset-data_registros_layoutv3 #model-index #autotrain_compatible #endpoints_compatible #region-us 

layoutlmv3-finetuned-registros\_100
===================================


This model was trained from scratch on the data\_registros\_layoutv3 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0050
* Precision: 0.9968
* Recall: 0.9951
* F1: 0.9960
* Accuracy: 0.9995


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: 600


### 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: 600 ### 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 #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: 600 ### Training results ### Framework versions


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