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-title: Submission Template
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-sdk: docker
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-
-# Logistic regression Model for Climate Disinformation Classification
-
-## Model Description
-
-This is a Logistic regression baseline model for the Frugal AI Challenge 2024, specifically for the text classification task of identifying climate disinformation. The model serves as a performance floor.
-
-### Intended Use
-
-- **Primary intended uses**: Baseline comparison for climate disinformation classification models
-- **Primary intended users**: Researchers and developers participating in the Frugal AI Challenge
-- **Out-of-scope use cases**: Not intended for production use or real-world classification tasks
-
-## Training Data
-
-The model uses the QuotaClimat/frugalaichallenge-text-train dataset:
-- Size: ~6000 examples
-- Split: 80% train, 20% test
-- 8 categories of climate disinformation claims
-
-### Labels
-0. No relevant claim detected
-1. Global warming is not happening
-2. Not caused by humans
-3. Not bad or beneficial
-4. Solutions harmful/unnecessary
-5. Science is unreliable
-6. Proponents are biased
-7. Fossil fuels are needed
-
-## Performance
-
-### Metrics
-- **Accuracy**: ~63.5% 
-- **Environmental Impact**:
-  - Emissions tracked in gCO2eq
-  - Energy consumption tracked in Wh
-
-### Model Architecture
-The model implements a random choice between the 8 possible labels, serving as the simplest possible baseline.
-
-## Environmental Impact
-
-Environmental impact is tracked using CodeCarbon, measuring:
-- Carbon emissions during inference
-- Energy consumption during inference
-
-This tracking helps establish a baseline for the environmental impact of model deployment and inference.
-
-## Limitations
-- Makes Logistic regression predictions
-- No learning or pattern recognition
-- Input text vectorized
-- Serves only as a LR baseline reference
-- Not suitable for any real-world applications
-
-## Ethical Considerations
-
-- Dataset contains sensitive topics related to climate disinformation
-- Model makes random predictions and should not be used for actual classification
-- Environmental impact is tracked to promote awareness of AI's carbon footprint
-```