Regenerative & Eco-Tourism: Travel focused on positive social and environmental impact
Integrated Wellness: Journeys combining physical and mental well-being
Immersive Culinary: Experiences centered on authentic local cuisine
Off-the-Beaten-Path Adventure: Exploration of less crowded natural landscapes

Performance

F1-Score: 0.9250
Accuracy: 0.9233
Precision: 0.9681
Recall: 0.8859

Training Details

Model: bert-base-uncased
Batch Size: 8
Learning Rate: 2e-05
Epochs: 5

Usage

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("j2damax/serendip-travel-classifier")
model = AutoModelForSequenceClassification.from_pretrained("j2damax/serendip-travel-classifier")

# Example text
text = "The organic tea plantation tour was amazing! We learned about sustainable farming practices."

# Tokenize and predict
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
with torch.no_grad():
    outputs = model(**inputs)
    predictions = torch.sigmoid(outputs.logits)

# Get predicted labels
labels = ["Regenerative & Eco-Tourism", "Integrated Wellness", "Immersive Culinary", "Off-the-Beaten-Path Adventure"]
predicted_labels = [labels[i] for i, score in enumerate(predictions[0]) if score > 0.5]
print(f"Predicted labels: predicted_labels")

Model Card

This model was trained on Sri Lankan tourism reviews to classify experiences into four categories. The model uses a multi-label classification approach, meaning a single review can be classified into multiple categories simultaneously.

Limitations

Trained specifically on Sri Lankan tourism data
May not generalize well to other geographical regions
Performance may vary with different text styles or languages

Citation

If you use this model, please cite:

bibtex

@misc{serendip-travel-classifier,
  title={Serendip Travel Experiential Classifier},
  author={Jayampathy Balasuriya},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/j2damax/serendip-travel-classifier}
}