| # eco-pulse-sentiment-analyzer | |
| ## Overview | |
| EcoPulse is a fine-tuned BERT model designed to analyze sentiment in environmental and climate change discourse. It categorizes text into Positive, Neutral, or Negative sentiments specifically regarding ecological health and policy updates. | |
| ## Model Architecture | |
| - **Base Model:** BERT-base-uncased | |
| - **Task:** Multi-class Sequence Classification | |
| - **Parameters:** 110M | |
| ## Intended Use | |
| - Analyzing public reaction to climate policy. | |
| - Monitoring environmental news trends. | |
| - Research in digital humanities regarding ecological sentiment. | |
| ## Limitations | |
| - Performance may degrade on highly technical scientific abstracts. | |
| - Sarcasm in climate activism tweets may be misclassified. | |
| ## Example Code | |
| ```python | |
| from transformers import pipeline | |
| classifier = pipeline("sentiment-analysis", model="eco-pulse-sentiment-analyzer") | |
| result = classifier("Renewable energy adoption reached record highs this quarter.") | |
| print(result) |