Sentiment Analysis Models
Collection
Collection of XLM-R-based Sentiment Analysis models trained on the data with two labels - positive and negative.
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Fine-tuned XLM-R Model for swahili Sentiment Analysis
This is a fine-tuned XLM-R model for sentiment analysis in swahili.
Model Details
- Model Name: XLM-R Sentiment Analysis
- Language: swahili
- Fine-tuning Dataset: DGurgurov/swahili_sa
Training Details
- Epochs: 20
- Batch Size: 32 (train), 64 (eval)
- Optimizer: AdamW
- Learning Rate: 5e-5
Performance Metrics
- Accuracy: 0.73684
- Macro F1: 0.42424
- Micro F1: 0.73684
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_swahili_sentiment")
model = AutoModelForSequenceClassification.from_pretrained("DGurgurov/xlm-r_swahili_sentiment")
License
[MIT]
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