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Detección de acoso en Twitter Español

This model is a fine-tuned version of 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
  • Luis Negrón
  • David Pacheco
  • Bryan Requenes
  • 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
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Dataset used to train hackathon-pln-es/Detect-Acoso-Twitter-Es

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