rasyosef / bert-medium-amharic-finetuned-sentiment

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Total runs: 2.5K
24-hour runs: 11
7-day runs: 65
30-day runs: 2.5K
Model's Last Updated: June 28 2024
text-classification

Introduction of bert-medium-amharic-finetuned-sentiment

Model Details of bert-medium-amharic-finetuned-sentiment

This model is a fine-tuned version of bert-medium-amharic on the amharic-sentiment dataset for sentiment classification . It achieves the following results on the evaluation set:

  • Accuracy: 0.83
  • Precision: 0.84
  • Recall: 0.83
  • F1: 0.83
How to use

You can use this model directly with a pipeline for text classification:

>>> from transformers import pipeline
>>> bert_sentiment = pipeline("text-classification", model="rasyosef/bert-medium-amharic-finetuned-sentiment")
>>> bert_sentiment(["አሪፍ ፊልም ነው።", "ዩክሬን እና ሩስያ ከባድ ውግያ ላይ ናቸው።"])

[{'label': 'positive', 'score': 0.9863048791885376},
 {'label': 'negative', 'score': 0.9570127129554749}]
Code

https://github.com/rasyosef/amharic-sentiment-classification

Runs of rasyosef bert-medium-amharic-finetuned-sentiment on huggingface.co

2.5K
Total runs
11
24-hour runs
35
3-day runs
65
7-day runs
2.5K
30-day runs

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