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--- |
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language: es |
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tags: |
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- "spanish" |
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metrics: |
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- accuracy |
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widget: |
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- text: "Eres mas pequeño que un pitufo!" |
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- text: "Eres muy feo!" |
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- text: "Odio tu forma de hablar!" |
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- text: "Eres tan fea que cuando eras pequeña te echaban de comer por debajo de la puerta." |
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--- |
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# roberta-base-bne-finetuned-ciberbullying-spanish |
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This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co./BSC-TeMU/roberta-base-bne) on the dataset generated scrapping all social networks (Twitter, Youtube ...) to detect ciberbullying on Spanish. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1657 |
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- Accuracy: 0.9607 |
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## Training and evaluation data |
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I use the concatenation from multiple datasets generated scrapping social networks (Twitter,Youtube,Discord...) to fine-tune this model. The total number of sentence pairs is above 360k sentences. |
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## Training procedure |
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<details> |
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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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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:-----:|:--------:|:---------------:| |
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| 0.1512 | 1.0 | 22227 | 0.9501 | 0.1418 | |
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| 0.1253 | 2.0 | 44454 | 0.9567 | 0.1499 | |
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| 0.0973 | 3.0 | 66681 | 0.9594 | 0.1397 | |
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| 0.0658 | 4.0 | 88908 | 0.9607 | 0.1657 | |
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</details> |
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### Model in action 🚀 |
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Fast usage with **pipelines**: |
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```python |
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from transformers import pipeline |
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model_path = "JonatanGk/roberta-base-bne-finetuned-ciberbullying-spanish" |
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bullying_analysis = pipeline("text-classification", model=model_path, tokenizer=model_path) |
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bullying_analysis( |
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"Desde que te vi me enamoré de ti." |
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) |
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# Output: |
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[{'label': 'Not_bullying', 'score': 0.9995710253715515}] |
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bullying_analysis( |
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"Eres tan fea que cuando eras pequeña te echaban de comer por debajo de la puerta." |
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) |
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# Output: |
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[{'label': 'Bullying', 'score': 0.9918262958526611}] |
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``` |
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JonatanGk/Shared-Colab/blob/master/Cyberbullying_detection_(SPANISH).ipynb) |
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### Framework versions |
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- Transformers 4.10.3 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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> Special thx to [Manuel Romero/@mrm8488](https://huggingface.co./mrm8488) as my mentor & R.C. |
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> Created by [Jonatan Luna](https://JonatanGk.github.io) | [LinkedIn](https://www.linkedin.com/in/JonatanGk/) |