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  This Hugging Face model card contains a machine learning model that uses fine-tuned mBERT to detect hate speech in Amharic language.
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  The model was fine-tuned using the Hugging Face Trainer API.
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  **<h1>Fine-Tuning</h1>**
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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 http://Davlan/bert-base-multilingual-cased-finetuned-amharic which was provided by Davlan on Huggingface.
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- **<h1>Dataset</h1>**
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- The model was fine-tuned on an Amharic Dataset that was made available by Mendeley Data (https://data.mendeley.com/datasets/ymtmxx385m).
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- The dataset contains 30,000 rows of Amharic text labeled as hate speech or not hate speech.
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  **<h1>Usage</h1>**
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  You can use the model through the Hugging Face Transformers library, either by directly loading the model in your Python code
 
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  This Hugging Face model card contains a machine learning model that uses fine-tuned mBERT to detect hate speech in Amharic language.
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  The model was fine-tuned using the Hugging Face Trainer API.
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  **<h1>Fine-Tuning</h1>**
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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 http://Davlan/bert-base-multilingual-cased-finetuned-amharic which was provided by Davlan on Huggingface.
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  **<h1>Usage</h1>**
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  You can use the model through the Hugging Face Transformers library, either by directly loading the model in your Python code