readme: ---
  language: 
    - amh
  tags:
  - Amharic
  - hate speech
  - sentiment analysis
  datasets:
  - https://data.mendeley.com/datasets/ymtmxx385m
  metrics:
  - F1
  - Accuracy
  ---
  
  **Amharic Hate Speech Detection using Fine-tuned mBERT**
  
  **Model description**
  
  This model was created by finetuning the RoBERTa model for the downstream task of Hate speech detection for the Amharic language.
  The initial RoBERTa model used for finetuning is israel/AmharicRoBERTa which was provided by Israel on Huggingface.
  The model was fine-tuned using HuggingFace's Trainer API. The final result of the finetuning has an F1-score of 0.9065 and an accuracy of 90.41%.
  The model was finetuned with 5 epochs and a learning rate of 0.00005.
  
  **Dataset description**
  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.
  
  **Other**
  The Google Colab notebook is made available on my GitHub. Check this path https://github.com/amengemeda/ISproject-2/blob/main/RoBERTa/Amharic_Hate_Speech_detection_using_fine_tuned_ROBERTA(Trainer_API).ipynb
  
  