---
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