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--- |
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license: cc-by-sa-4.0 |
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base_model: jcblaise/roberta-tagalog-base |
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tags: |
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- generated_from_trainer |
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- tagalog |
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- filipino |
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- twitter |
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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-base-philippine-elections-2016-2022-hate-speech |
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results: [] |
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datasets: |
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- hate_speech_filipino |
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- mapsoriano/2016_2022_hate_speech_filipino |
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language: |
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- tl |
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- en |
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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-base-philippine-elections-2016-2022-hate-speech |
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This model is a fine-tuned version of [jcblaise/roberta-tagalog-base](https://huggingface.co/jcblaise/roberta-tagalog-base) for the task of Text Classification, classifying hate and non-hate tweets. |
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The model was fine-tuned on a combined dataset [mapsoriano/2016_2022_hate_speech_filipino](https://huggingface.co/datasets/mapsoriano/2016_2022_hate_speech_filipino) consisting of |
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the [hate_speech_filipino](https://huggingface.co/datasets/hate_speech_filipino) dataset and a newly crawled 2022 Philippine Presidential Elections-related Tweets Hate Speech Dataset. |
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It achieves the following results on the evaluation (validation) set: |
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- Loss: 0.3574 |
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- Accuracy: 0.8743 |
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It achieves the following results on the test set: |
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- Accuracy: 0.8783 |
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- Precision: 0.8563 |
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- Recall: 0.9077 |
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- F1: 0.8813 |
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Feel free to connect via [LinkedIn](https://www.linkedin.com/in/map-soriano/) for further information on this model or on the study that it was used on. |
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<!-- ## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed --> |
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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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- num_epochs: 2 |
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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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| 0.3423 | 1.0 | 1361 | 0.3167 | 0.8693 | |
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| 0.2194 | 2.0 | 2722 | 0.3574 | 0.8743 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
