#HackathonSomosNLP 22: Cool Projects
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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 hackathon-pln-es/Dataset-Acoso-Twitter-Es.
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
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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