readme: ---
  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
  