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--- |
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language: es |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- es |
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- text-classification |
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- acoso |
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- twitter |
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- cyberbullying |
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datasets: |
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- hackathon-pln-es/Dataset-Acoso-Twitter-Es |
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metrics: |
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- accuracy |
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widget: |
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- text: Que horrible como la farándula chilena siempre se encargaba de dejar mal a |
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las mujeres. Un asco |
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- text: Hay que ser bien menestra para amenazar a una mujer con una llave de ruedas. |
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Viendo como se viste no me queda ninguna duda |
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- text: más centrados en tener una sociedad reprimida y sumisa que en estudiar y elaborar |
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políticas de protección hacia las personas de mayor riesgo ante el virus. |
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base_model: mrm8488/distilroberta-finetuned-tweets-hate-speech |
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model-index: |
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- name: Detección de acoso en Twitter |
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results: [] |
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--- |
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# Detección de acoso en Twitter Español |
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This model is a fine-tuned version of [mrm8488/distilroberta-finetuned-tweets-hate-speech](https://huggingface.co/mrm8488/distilroberta-finetuned-tweets-hate-speech) on [hackathon-pln-es/Dataset-Acoso-Twitter-Es](https://huggingface.co/datasets/hackathon-pln-es/Dataset-Acoso-Twitter-Es). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1628 |
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- Accuracy: 0.9167 |
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# UNL: Universidad Nacional de Loja |
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## Miembros del equipo: |
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- Anderson Quizhpe <br> |
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- Luis Negrón <br> |
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- David Pacheco <br> |
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- Bryan Requenes <br> |
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- Paul Pasaca |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6732 | 1.0 | 27 | 0.3797 | 0.875 | |
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| 0.5537 | 2.0 | 54 | 0.3242 | 0.9167 | |
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| 0.5218 | 3.0 | 81 | 0.2879 | 0.9167 | |
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| 0.509 | 4.0 | 108 | 0.2606 | 0.9167 | |
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| 0.4196 | 5.0 | 135 | 0.1628 | 0.9167 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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