metadata

dataset_info:
  features:
    - name: headline
      dtype: string
    - name: category
      dtype: string
    - name: date
      dtype: string
    - name: views
      dtype: string
    - name: article
      dtype: string
    - name: link
      dtype: string
    - name: word_len
      dtype: int64
    - name: label
      dtype:
        class_label:
          names:
            '0': ሀገር አቀፍ ዜና
            '1': መዝናኛ
            '2': ስፖርት
            '3': ቢዝነስ
            '4': ዓለም አቀፍ ዜና
            '5': ፖለቲካ
  splits:
    - name: train
      num_bytes: 191486316
      num_examples: 49971
  download_size: 86414046
  dataset_size: 191486316
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - text-classification
  - summarization
language:
  - am
size_categories:
  - 10K<n<100K

Amharic News Category Classification

This amharic text dataset can be used to train/finetune models for the following tasks

classification : using the categories
summarization : using the headlines

Finetuning

Here is a github repo that contains three notebooks that use this dataset to finetune the following models.

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

https://github.com/rasyosef/amharic-news-category-classification

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)

Fine-tuned Model Performance

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

Original CSV and Paper

The original csv file can be found in this git repository https://github.com/IsraelAbebe/An-Amharic-News-Text-classification-Dataset

Paper: https://arxiv.org/abs/2103.05639

While there is a version of this dataset that's already available on huggingface hub (israel/Amharic-News-Text-classification-Dataset), that version had been preprocessed to remove punctuation from the articles, while this version contains the entire text along with punctuations. As a result, this version is more preferable for finetuning transformer models.