| --- |
| library_name: sentence-transformers |
| pipeline_tag: sentence-similarity |
| tags: |
| - sentence-transformers |
| - biblical-search |
| - semantic-search |
| - embeddinggemma |
| - fine-tuned |
| license: apache-2.0 |
| datasets: |
| - biblical-text-pairs |
| metrics: |
| - accuracy@1: 12.00% |
| - accuracy@3: 15.00% |
| - accuracy@10: 31.00% |
| language: |
| - en |
| --- |
| |
| # EmbeddingGemma-300M Fine-tuned for Biblical Text Search |
|
|
| This model is a fine-tuned version of [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m) specialized for biblical text search and retrieval. |
|
|
| ## Model Performance |
|
|
| - **Accuracy@1**: 12.00% (13x improvement over base model) |
| - **Accuracy@3**: 15.00% |
| - **Accuracy@10**: 31.00% |
| - **Training Steps**: 25 (optimal stopping point) |
| - **Base Model Accuracy@1**: 0.91% |
|
|
| ## Usage |
|
|
| ```python |
| from sentence_transformers import SentenceTransformer |
| |
| # Load the model |
| model = SentenceTransformer('dpshade22/embeddinggemma-scripture-v1') |
| |
| # Encode queries (use search_query: prefix) |
| query = "search_query: What is love?" |
| query_embedding = model.encode([query]) |
| |
| # Encode documents (use search_document: prefix) |
| document = "search_document: Love is patient and kind" |
| doc_embedding = model.encode([document]) |
| ``` |
|
|
| ## Prefixes |
|
|
| For optimal performance, use these prefixes: |
|
|
| - **Queries**: `"search_query: your question here"` |
| - **Documents**: `"search_document: scripture text here"` |
|
|
| ## Training Details |
|
|
| - **Training Data**: 26,276 biblical text pairs |
| - **Learning Rate**: 2.0e-04 |
| - **Batch Size**: 8 |
| - **Training Strategy**: Early stopping at 25 steps to prevent overfitting |
| - **Output Dimensions**: 768D (supports Matryoshka 384D, 128D) |
|
|
| ## Intended Use |
|
|
| This model is designed for: |
| - Biblical text search and retrieval |
| - Finding relevant scripture passages |
| - Semantic similarity of religious texts |
| - Question answering on biblical topics |
|
|
