metadata

library_name: peft
base_model: xlm-roberta-base
license: mit
language:
  - am
metrics:
  - accuracy
  - f1
pipeline_tag: text-classification

xlm-roberta-base-lora-amharic-news-classification

This repo contains LoRA adapters for the xlm-roberta-base model finetuned on the Amharic-News-Text-classification-Dataset.

The finetuned model classifies an 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)

It achieves the following results on the evaluation set:

Train Loss: 0.3447
Validation Loss: 0.3947
Validation Accuracy: 0.8541
Validation F1 Score (macro): 0.8105
Validation F1 Score (weighted): 0.8551

How to use

You can use this model with a pipeline for text classification. But first, you need to install the peft library like so:

pip install peft

Then, you can run the following code.

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_id = "xlm-roberta-base"
peft_model_id = "rasyosef/xlm-roberta-base-lora-amharic-news-classification" 

categories = ['ሀገር አቀፍ ዜና', 'መዝናኛ', 'ስፖርት', 'ቢዝነስ', 'ዓለም አቀፍ ዜና', 'ፖለቲካ']
id2label = {i: lbl for i, lbl in enumerate(categories)}
label2id = {lbl: i for i, lbl in enumerate(categories)}

tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForSequenceClassification.from_pretrained(
    model_id, 
    num_labels=len(categories), # 6
    id2label=id2label,
    label2id=label2id
)

model.load_adapter(peft_model_id)

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

classifier([
  """ቅርሶቹን ለመታደግ የተጀመረው የሙዚዬም ግንባታም በበጀት ምክንያት ተቋርጧል።
  
  በአፄ ቴዎድሮስ የንግስና ቦታ ደረስጌ ማሪያም ተጀምሮ የቆመው የሙዚየሙ ግንባታ ተጠናቀቆ ስራ 
  እንዲጀምር ነዋሪዎች ጠይቀዋል። ዘመነ መሳፍንት መቋጫ ያገኘባት የኢትዮጵያ አንድነት የታወጀባት ዳግማዊ 
  አፄ ቴዎድሮስ ከመንገሳቸው በፊት ደጃች ውቤን ቧሂት ከሚባል ቦታ ድል አድርገው ደጃች ውቤ ለንግስና ባዘጋጁት የንግስና ቦታና 
  እቃዎች ንጉሰ ነገስት ዘኢትዮጵያ ተብለው የነገሱባት ቦታ ናት።""", # 'ሀገር አቀፍ ዜና'
])

Output:

[{'label': 'ሀገር አቀፍ ዜና', 'score': 0.977573037147522}]

Model Details

Model Description

Developed by: [More Information Needed]
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Model type: [More Information Needed]
Language(s) (NLP): [More Information Needed]
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Finetuned from model [optional]: [More Information Needed]

Framework versions

PEFT 0.7.1