---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: roberta-bne-clara
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-bne-clara

This model is a fine-tuned version of [roberta-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the Diario de Madrid dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2078
- F1: 0.5174
- Precision: 0.4561
- Recall: 0.5977

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.7026        | 1.0   | 103  | 0.2844          | 0.4720 | 0.5135    | 0.4368 |
| 0.325         | 2.0   | 206  | 0.1715          | 0.5665 | 0.5698    | 0.5632 |
| 0.2094        | 3.0   | 309  | 0.1452          | 0.6294 | 0.5636    | 0.7126 |
| 0.1416        | 4.0   | 412  | 0.1508          | 0.5178 | 0.4636    | 0.5862 |
| 0.1058        | 5.0   | 515  | 0.1794          | 0.5700 | 0.4917    | 0.6782 |
| 0.0711        | 6.0   | 618  | 0.1743          | 0.5510 | 0.4954    | 0.6207 |
| 0.0489        | 7.0   | 721  | 0.1900          | 0.5895 | 0.5437    | 0.6437 |
| 0.0373        | 8.0   | 824  | 0.1841          | 0.6131 | 0.5446    | 0.7011 |
| 0.0277        | 9.0   | 927  | 0.1954          | 0.5445 | 0.5       | 0.5977 |
| 0.0215        | 10.0  | 1030 | 0.2078          | 0.5174 | 0.4561    | 0.5977 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 1.16.1
- Tokenizers 0.13.2