rasyosef/amharic-sentiment
Viewer • Updated • 2.78k • 49 • 1
How to use rasyosef/bert-medium-amharic-finetuned-sentiment with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="rasyosef/bert-medium-amharic-finetuned-sentiment") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("rasyosef/bert-medium-amharic-finetuned-sentiment")
model = AutoModelForSequenceClassification.from_pretrained("rasyosef/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: 0.83Precision: 0.84Recall: 0.83F1: 0.83You 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}]
https://github.com/rasyosef/amharic-sentiment-classification