| --- |
| license: cc-by-sa-4.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: roberta-tagalog-profanity-classifier |
| 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. --> |
|
|
| # roberta-tagalog-profanity-classifier |
|
|
| This model is a fine-tuned version of [jcblaise/roberta-tagalog-base](https://huggingface.co/jcblaise/roberta-tagalog-base) on [mginoben/tagalog-profanity-dataset](https://huggingface.co/datasets/mginoben/tagalog-profanity-dataset) dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3019 |
| - Accuracy: 0.8898 |
| - Precision: 0.8523 |
| - Recall: 0.8944 |
| - F1: 0.8728 |
|
|
| ## Model description |
|
|
| The Model classifies tagalog texts that contains profanities as either Abusive or Non-Abusive. |
|
|
| It only classifies texts with the following profanities: |
| - bobo |
| - bwiset |
| - gago |
| - kupal |
| - pakshet |
| - pakyu |
| - pucha |
| - punyeta |
| - puta |
| - putangina |
| - tanga |
| - tangina |
| - tarantado |
| - ulol |
|
|
| ## Intended uses & limitations |
|
|
| For content moderation accross different social medias |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | No log | 1.0 | 174 | 0.3006 | 0.8776 | 0.8620 | 0.8458 | 0.8538 | |
| | No log | 2.0 | 348 | 0.2899 | 0.8834 | 0.8801 | 0.8382 | 0.8586 | |
| | 0.2993 | 3.0 | 522 | 0.2869 | 0.8873 | 0.8491 | 0.8918 | 0.8700 | |
| | 0.2993 | 4.0 | 696 | 0.3019 | 0.8898 | 0.8523 | 0.8944 | 0.8728 | |
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|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
