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---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
- generated_from_trainer
datasets:
- fact2020
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-bne-finetuned-fact
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: fact2020
type: fact2020
config: fact2020
split: validation
args: fact2020
metrics:
- name: Precision
type: precision
value: 0.9952769966107677
- name: Recall
type: recall
value: 0.9906410661303304
- name: F1
type: f1
value: 0.9911413895764224
- name: Accuracy
type: accuracy
value: 0.9906410661303304
language:
- es
pipeline_tag: token-classification
widget:
- text: "Guatemala sufre y llora a sus fallecidos bajo un manto negro de ceniza."
- text: "La estrategia se ejecuta, no se cuenta."
---
<!-- 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-finetuned-fact
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 fact2020 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0368
- Precision: 0.9953
- Recall: 0.9906
- F1: 0.9911
- Accuracy: 0.9906
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 116 | 0.0404 | 0.9945 | 0.9899 | 0.9901 | 0.9899 |
| No log | 2.0 | 232 | 0.0359 | 0.9948 | 0.9903 | 0.9906 | 0.9903 |
| No log | 3.0 | 348 | 0.0368 | 0.9953 | 0.9906 | 0.9911 | 0.9906 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3 |