pytorch tensorboard roberta text-classification es dataset:hackathon-pln-es/Dataset-Acoso-Twitter-Es transformers generated_from_trainer acoso twitter cyberbullying license:apache-2.0 model-index
---
license: apache-2.0
language: "es"
tags:
- generated_from_trainer
- es
- text-classification
- acoso
- twitter
- cyberbullying 
datasets:
- hackathon-pln-es/Dataset-Acoso-Twitter-Es
widget:
- text: "Que horrible como la farándula chilena siempre se encargaba de dejar mal a las mujeres. Un asco"
- text: "Hay que ser bien menestra para amenazar a una mujer con una llave de ruedas. Viendo como se viste no me queda ninguna duda"
- text: "más centrados en tener una sociedad reprimida y sumisa que en estudiar y elaborar políticas de protección hacia las personas de mayor riesgo ante el virus."

metrics:
- accuracy
model-index:
- name: Detección de acoso en Twitter
  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. -->

# Detección de acoso en Twitter Español

This model is a fine-tuned version of [mrm8488/distilroberta-finetuned-tweets-hate-speech](https://huggingface.co/mrm8488/distilroberta-finetuned-tweets-hate-speech) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1628
- Accuracy: 0.9167

# UNL: Universidad Nacional de Loja

## Miembros del equipo:
- Anderson Quizhpe <br>
- Luis Negrón <br>
- David Pacheco <br>
- Bryan Requenes <br>
- Paul Pasaca

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6732        | 1.0   | 27   | 0.3797          | 0.875    |
| 0.5537        | 2.0   | 54   | 0.3242          | 0.9167   |
| 0.5218        | 3.0   | 81   | 0.2879          | 0.9167   |
| 0.509         | 4.0   | 108  | 0.2606          | 0.9167   |
| 0.4196        | 5.0   | 135  | 0.1628          | 0.9167   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
