---
license: mit
base_model: filevich/robertita-cased
tags:
- generated_from_trainer
datasets:
- fact2020
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robertita-cased-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: 0.9946938891717209
    - name: Recall
      type: recall
      value: 0.988775334205079
    - name: F1
      type: f1
      value: 0.9893166033671081
    - name: Accuracy
      type: accuracy
      value: 0.988775334205079
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. -->

# robertita-cased-finetuned-fact

This model is a fine-tuned version of [filevich/robertita-cased](https://huggingface.co/filevich/robertita-cased) on the fact2020 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0407
- Precision: 0.9947
- Recall: 0.9888
- F1: 0.9893
- Accuracy: 0.9888

## 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  | 0.0554          | 0.9909    | 0.9817 | 0.9807 | 0.9817   |
| No log        | 2.0   | 232  | 0.0415          | 0.9943    | 0.9879 | 0.9882 | 0.9879   |
| No log        | 3.0   | 348  | 0.0407          | 0.9947    | 0.9888 | 0.9893 | 0.9888   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3