---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-bne-ner
  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. -->

# roberta-base-bne-ner

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3159
- Precision: 0.8517
- Recall: 0.8933
- F1: 0.8720
- Accuracy: 0.9384

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 280  | 0.3006          | 0.7961    | 0.8563 | 0.8251 | 0.9164   |
| 0.4008        | 2.0   | 560  | 0.2984          | 0.7918    | 0.8622 | 0.8255 | 0.9203   |
| 0.4008        | 3.0   | 840  | 0.2324          | 0.8401    | 0.8563 | 0.8481 | 0.9343   |
| 0.1014        | 4.0   | 1120 | 0.2394          | 0.8242    | 0.8889 | 0.8553 | 0.9414   |
| 0.1014        | 5.0   | 1400 | 0.2674          | 0.8469    | 0.8933 | 0.8695 | 0.9371   |
| 0.0435        | 6.0   | 1680 | 0.2815          | 0.8255    | 0.8830 | 0.8533 | 0.9375   |
| 0.0435        | 7.0   | 1960 | 0.2713          | 0.8516    | 0.8844 | 0.8677 | 0.9444   |
| 0.0233        | 8.0   | 2240 | 0.2745          | 0.8541    | 0.8933 | 0.8733 | 0.9437   |
| 0.0177        | 9.0   | 2520 | 0.3383          | 0.8336    | 0.8978 | 0.8645 | 0.9350   |
| 0.0177        | 10.0  | 2800 | 0.2858          | 0.8606    | 0.8963 | 0.8781 | 0.9419   |
| 0.013         | 11.0  | 3080 | 0.2956          | 0.8350    | 0.8919 | 0.8625 | 0.9403   |
| 0.013         | 12.0  | 3360 | 0.3097          | 0.8423    | 0.9022 | 0.8712 | 0.9380   |
| 0.0104        | 13.0  | 3640 | 0.3158          | 0.8443    | 0.8919 | 0.8674 | 0.9380   |
| 0.0104        | 14.0  | 3920 | 0.3171          | 0.8493    | 0.8933 | 0.8708 | 0.9387   |
| 0.0088        | 15.0  | 4200 | 0.3159          | 0.8517    | 0.8933 | 0.8720 | 0.9384   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1