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language: |
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- amh |
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tags: |
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- Amharic |
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- hate speech |
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- sentiment analysis |
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datasets: |
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- https://data.mendeley.com/datasets/ymtmxx385m |
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metrics: |
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- F1 |
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- Accuracy |
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**Amharic Hate Speech Detection using Fine-tuned mBERT** |
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**Model description** |
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This model was created by finetuning the mBERT model for the downstream task of Hate speech detection for the Amharic language. |
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The initial mBERT model used for finetuning is Davlan/bert-base-multilingual-cased-finetuned-amharic which was provided by Davlan on Huggingface. |
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The model was fine-tuned using HuggingFace's Trainer API. The final result of the finetuning has an F1-score of 0.9172 and an accuracy of 91.59%. |
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The model was finetuned with 15 epochs and a learning rate of 0.00005. |
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**Dataset description** |
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The finetuning was done on an Amharic Dataset that was made available by Mendeley Data (https://data.mendeley.com/datasets/ymtmxx385m). It has a size of 30,000 rows. |
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**Other** |
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The Google Colab notebook is made available on my GitHub. Check this path https://github.com/amengemeda/ISproject-2/blob/main/mBERT/Amharic_Hate_Speech_detection_using_mBERT_(Trainer_API).ipynb |
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