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 mBERT model for the downstream task of Hate speech detection for the Amharic language.
  The initial mBERT model used for finetuning is Davlan/bert-base-multilingual-cased-finetuned-amharic which was provided by Davlan on Huggingface.
  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%.
  The model was finetuned with 15 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/mBERT/Amharic_Hate_Speech_detection_using_mBERT_(Trainer_API).ipynb
  