---
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
datasets:
- conll2002
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-1
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: conll2002
      type: conll2002
      config: es
      split: validation
      args: es
    metrics:
    - name: Precision
      type: precision
      value: 0.805356
    - name: Recall
      type: recall
      value: 0.822381
    - name: F1
      type: f1
      value: 0.813779
    - name: Accuracy
      type: accuracy
      value: 0.969573
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-finetuned-ner-1

Este es modelo resultado de un finetuning de 
[google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) sobre el conll2002 dataset.
Los siguientes son los resultados sobre el conjunto de evaluación:
- Training Loss: 0.000900
- Validation Loss: 0.306902
- Precision: 0.805356
- Recall: 0.822381
- F1: 0.813779
- Accuracy: 0.969573


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- num_epochs: 8
- weight_decay: 0.001

### Training results

| Epoch | Training Loss | Validation Loss | Precision | Recall  | F1      | Accuracy |
|:-----:|:-------------:|:---------------:|:---------:|:-------:|:-------:|:--------:|
| 1.0   | 0.0045        | 0.263534        | 0.787187  | 0.815947| 0.801309| 0.968117 |
| 2.0   | 0.0054        | 0.261010        | 0.776933  | 0.798713| 0.787673| 0.966914 |
| 3.0   | 0.0031        | 0.288264        | 0.787994  | 0.811351| 0.799502| 0.967351 |
| 4.0   | 0.0030        | 0.261651        | 0.799186  | 0.812040| 0.805562| 0.969476 |
| 5.0   | 0.0023        | 0.281675        | 0.792880  | 0.813649| 0.803130| 0.968544 |
| 6.0   | 0.0014        | 0.285965        | 0.790842  | 0.817555| 0.803977| 0.969311 |
| 7.0   | 0.0009        | 0.320790        | 0.795583  | 0.811121| 0.803277| 0.968049 |
| 8.0   | 0.0009        | 0.306902        | 0.805356  | 0.822381| 0.813779| 0.969573 |