---
language:
- es
tags:
- generated_from_trainer
datasets:
- jorgeortizfuentes/spanish_nominal_groups_conll2003
model-index:
- name: nominal-groups-recognition-bert-base-spanish-wwm-cased
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# nominal-groups-recognition-bert-base-spanish-wwm-cased

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co./dccuchile/bert-base-spanish-wwm-cased) on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3568
- Ng Precision: 0.7280
- Ng Recall: 0.7767
- Ng F1: 0.7516
- Ng Number: 3198
- Overall Precision: 0.7280
- Overall Recall: 0.7767
- Overall F1: 0.7516
- Overall Accuracy: 0.8992

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 13
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Ng Precision | Ng Recall | Ng F1  | Ng Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:------:|:---------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.3955        | 1.0   | 228  | 0.2778          | 0.7129       | 0.7492    | 0.7306 | 3198      | 0.7129            | 0.7492         | 0.7306     | 0.8924           |
| 0.2186        | 2.0   | 456  | 0.2763          | 0.7318       | 0.7711    | 0.7509 | 3198      | 0.7318            | 0.7711         | 0.7509     | 0.8990           |
| 0.1586        | 3.0   | 684  | 0.2960          | 0.7274       | 0.7733    | 0.7496 | 3198      | 0.7274            | 0.7733         | 0.7496     | 0.8992           |
| 0.119         | 4.0   | 912  | 0.3330          | 0.7283       | 0.7727    | 0.7498 | 3198      | 0.7283            | 0.7727         | 0.7498     | 0.8982           |
| 0.0943        | 5.0   | 1140 | 0.3568          | 0.7280       | 0.7767    | 0.7516 | 3198      | 0.7280            | 0.7767         | 0.7516     | 0.8992           |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3