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--- |
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license: cc-by-sa-4.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: roberta-tagalog-profanity-classifier |
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results: [] |
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base_model: https://huggingface.co/jcblaise/roberta-tagalog-base |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-tagalog-profanity-classifier |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3019 |
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- Accuracy: 0.8898 |
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- Precision: 0.8523 |
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- Recall: 0.8944 |
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- F1: 0.8728 |
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## Model description |
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The Model classifies tagalog texts that contains profanities as either Abusive or Non-Abusive. |
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It only classifies texts with the following profanities: |
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- bobo |
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- bwiset |
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- gago |
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- kupal |
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- pakshet |
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- pakyu |
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- pucha |
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- punyeta |
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- puta |
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- putangina |
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- tanga |
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- tangina |
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- tarantado |
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- ulol |
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## Intended uses & limitations |
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For content moderation accross different social medias |
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## Training and evaluation data |
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- Training: 11,110 |
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- Validation: 2,778 |
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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: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 174 | 0.3006 | 0.8776 | 0.8620 | 0.8458 | 0.8538 | |
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| No log | 2.0 | 348 | 0.2899 | 0.8834 | 0.8801 | 0.8382 | 0.8586 | |
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| 0.2993 | 3.0 | 522 | 0.2869 | 0.8873 | 0.8491 | 0.8918 | 0.8700 | |
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| 0.2993 | 4.0 | 696 | 0.3019 | 0.8898 | 0.8523 | 0.8944 | 0.8728 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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