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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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  **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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  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.