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--- |
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language: |
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- am |
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metrics: |
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- accuracy |
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- f1 |
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library_name: transformers |
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pipeline_tag: text-classification |
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tags: |
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- Sentiment-Analysis |
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- Hate-Speech |
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- Finetuning-mBERT |
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--- |
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**<h1>Hate-Speech-Detection-in-Amharic-Language-mBERT</h1>** |
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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 |
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or by using the Hugging Face model hub. |
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