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Fine-tuned XLM-R Model for amharic Sentiment Analysis
This is a fine-tuned XLM-R model for sentiment analysis in amharic.
Model Details
- Model Name: XLM-R Sentiment Analysis
- Language: amharic
- Fine-tuning Dataset: DGurgurov/amharic_sa
Training Details
- Epochs: 20
- Batch Size: 32 (train), 64 (eval)
- Optimizer: AdamW
- Learning Rate: 5e-5
Performance Metrics
- Accuracy: 0.86842
- Macro F1: 0.86833
- Micro F1: 0.86842
Usage
To use this model, you can load it with the Hugging Face Transformers library:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("DGurgurov/xlm-r_amharic_sentiment")
model = AutoModelForSequenceClassification.from_pretrained("DGurgurov/xlm-r_amharic_sentiment")
License
[MIT]
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