- Created `n00 Beir Analysis_cosqa.ipynb` for analyzing CoSQA dataset with BEIR.
- Created `n00 first Analysis.ipynb` for initial analysis with embeddings.
- Implemented `evaluate_embeddings_pipeline.py` to evaluate embedding models across CodexGlue, CoSQA, and SciFact benchmarks.
- Added adapters for Ollama and HuggingFace embeddings to ensure compatibility with BEIR.
- Enhanced error handling and data normalization in embedding processes.
- Included functionality to load datasets from local cache or download if not present.
- Created `n00 Beir Analysis.ipynb` for analyzing BEIR dataset with Ollama embeddings.
- Added `n00 Beir Analysis_cosqa.ipynb` for evaluating the CosQA dataset using similar embedding techniques.
- Introduced `n00 first Analysis.ipynb` for initial analysis with Ragas embeddings and semantic similarity evaluation.
- Implemented data loading and processing for each notebook, including downloading datasets and saving results.
- Included evaluation metrics such as NDCG, MAP, Recall, and Precision for model performance assessment.
pseco
acano