---
library_name: transformers
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-large-bne-capitel-ner
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-bne-capitel-ner-finetuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: biobert_json
      type: biobert_json
      config: Biobert_json
      split: validation
      args: Biobert_json
    metrics:
    - name: Precision
      type: precision
      value: 0.9574114124105806
    - name: Recall
      type: recall
      value: 0.9658741258741259
    - name: F1
      type: f1
      value: 0.961624150607107
    - name: Accuracy
      type: accuracy
      value: 0.9810238869097464
---

<!-- 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. -->

# roberta-large-bne-capitel-ner-finetuned-ner

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-large-bne-capitel-ner](https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne-capitel-ner) on the biobert_json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0918
- Precision: 0.9574
- Recall: 0.9659
- F1: 0.9616
- Accuracy: 0.9810

## 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: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1292        | 1.0   | 1224 | 0.0942          | 0.9455    | 0.9528 | 0.9491 | 0.9737   |
| 0.0813        | 2.0   | 2448 | 0.0960          | 0.9443    | 0.9696 | 0.9568 | 0.9780   |
| 0.0509        | 3.0   | 3672 | 0.0819          | 0.9559    | 0.9686 | 0.9622 | 0.9814   |
| 0.0314        | 4.0   | 4896 | 0.0853          | 0.9557    | 0.9694 | 0.9625 | 0.9811   |
| 0.0196        | 5.0   | 6120 | 0.0918          | 0.9574    | 0.9659 | 0.9616 | 0.9810   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3