This github repo that contains three notebooks that use the amharic-news-category-classification dataset to finetune the following models for a text classification task.
The finetuned model classifies a given Amharic news article into one of the following 6 categories.
- ሀገር አቀፍ ዜና (Local News)
- መዝናኛ (Entertainment)
- ስፖርት (Sports)
- ቢዝነስ (Business)
- ዓለም አቀፍ ዜና (International News)
- ፖለቲካ (Politics)
- xlm-roberta-base : a multilingual transformer model with 280M parameters
- bert-small-amharic : a new amharic version of the bert-small transformer model with 25.7M parameters, pretrained from scratch using unlabelled amharic text data
- bert-mini-amharic : a new amharic version of the bert-mini transformer model with 9.67M parameters, pretrained from scratch using unlabelled amharic text data
Since this is a multi-class classification task, the reported precision, recall, and f1 metrics are macro averages.
| Model | Size (# params) | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|
| xlm-roberta-base | 279M | 0.9 | 0.88 | 0.88 | 0.88 |
| bert-small-amharic | 25.7M | 0.89 | 0.86 | 0.87 | 0.86 |
| bert-mini-amharic | 9.67M | 0.87 | 0.83 | 0.83 | 0.83 |