---
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: 0.2988
- Ng Precision: 0.7309
- Ng Recall: 0.7780
- Ng F1: 0.7537
- Ng Number: 3198
- Overall Precision: 0.7309
- Overall Recall: 0.7780
- Overall F1: 0.7537
- Overall Accuracy: 0.9019

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:------:|:---------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.451         | 1.0   | 114  | 0.2882          | 0.6985       | 0.7483    | 0.7225 | 3198      | 0.6985            | 0.7483         | 0.7225     | 0.8899           |
| 0.2429        | 2.0   | 228  | 0.2917          | 0.7294       | 0.7483    | 0.7387 | 3198      | 0.7294            | 0.7483         | 0.7387     | 0.8932           |
| 0.193         | 3.0   | 342  | 0.2864          | 0.7306       | 0.7727    | 0.7511 | 3198      | 0.7306            | 0.7727         | 0.7511     | 0.9000           |
| 0.1586        | 4.0   | 456  | 0.2988          | 0.7309       | 0.7780    | 0.7537 | 3198      | 0.7309            | 0.7780         | 0.7537     | 0.9019           |
| 0.1386        | 5.0   | 570  | 0.3116          | 0.7275       | 0.7770    | 0.7514 | 3198      | 0.7275            | 0.7770         | 0.7514     | 0.9003           |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3