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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- biencoder |
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- sentence-transformers |
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- text-classification |
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- sentence-pair-classification |
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- semantic-similarity |
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- semantic-search |
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- retrieval |
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- reranking |
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- generated_from_trainer |
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- dataset_size:400 |
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- loss:AdaFaceInBatchLoss |
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base_model: Alibaba-NLP/gte-modernbert-base |
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widget: |
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- source_sentence: The aversive or evitative case ( abbreviated ) is a grammatical |
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case that is found in Australian Aboriginal languages and indicates that the marked |
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noun is avoided or feared . |
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sentences: |
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- The aversive or evitative case ( abbreviated ) is a grammatical case that is found |
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in Australian Aboriginal languages and indicates that the marked noun is avoided |
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or feared . |
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- He was born in Ryno , Johannesburg , died in North West . |
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- The aversive or evitative case ( abbreviated ) is a marked case found in Australian |
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Aboriginal languages that indicates that the grammatical noun is avoided or feared |
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. |
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- source_sentence: Three ships of the Royal Australian Navy ( RAN ) were named after |
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Perth , the capital city of Western Australia , as HMAS `` Perth `` . |
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sentences: |
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- Three ships of the Royal Australian Navy ( RAN ) have been named HMAS `` Western |
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Australia `` after Perth , the capital city of Perth . |
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- Three ships of the Royal Australian Navy ( RAN ) were named after Perth , the |
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capital city of Western Australia , as HMAS `` Perth `` . |
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- He lost the title to Rees after Iestyn Rees purchased his title shot at PWE Jingle |
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All The Galloway . |
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- source_sentence: Oxynoe azuropunctata is a kind of small sea snail or sea snail |
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, a bubble snail , a marine gastropod mollusk in the Oxynoidae family . |
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sentences: |
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- It is located at Ellison Bay , in the town of Liberty Grove , Wisconsin . |
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- Oxynoe azuropunctata is a kind of small sea snail or sea snail , a bubble snail |
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, a marine gastropod mollusk in the Oxynoidae family . |
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- Oxynoe azuropunctata is a species of marine sea snail or sea slug , a bubble snail |
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, a small gastropod mollusk in the family Oxynoidae . |
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- source_sentence: It included the original six tracks , re-worked with new vocals |
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and live drums , three remixes , and new two tracks . |
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sentences: |
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- It included the original six tracks , overhauled with new vocals and live drums |
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, three remixes and two new tracks . |
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- Punish Lichfield , garrison Birmingham , and clear the country as far as possible |
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. |
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- Antoninus , or known as Antoninus , was a Roman who lived in the 1st century . |
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- source_sentence: It is known from Australia , including South Australia , Tasmania |
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, Queensland , New South Wales and Victoria . |
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sentences: |
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- It is famous from Australia , including South Australia , Tasmania , Queensland |
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, New South Wales and Victoria . |
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- In 1995 Franz married Joanie Zeck , whom he met in 1982 . |
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- In 1792 , the family moved to Kingston in Toronto and then York ( later renamed |
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Upper Canada ) . |
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datasets: |
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- redis/langcache-sentencepairs-v2 |
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pipeline_tag: sentence-similarity |
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library_name: sentence-transformers |
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metrics: |
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- cosine_accuracy@1 |
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- cosine_precision@1 |
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- cosine_recall@1 |
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- cosine_ndcg@10 |
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- cosine_mrr@1 |
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- cosine_map@100 |
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model-index: |
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- name: Redis fine-tuned BiEncoder model for semantic caching on LangCache |
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results: |
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- task: |
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type: information-retrieval |
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name: Information Retrieval |
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dataset: |
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name: test |
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type: test |
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metrics: |
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- type: cosine_accuracy@1 |
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value: 0.5861241448475948 |
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name: Cosine Accuracy@1 |
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- type: cosine_precision@1 |
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value: 0.5861241448475948 |
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name: Cosine Precision@1 |
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- type: cosine_recall@1 |
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value: 0.5679885764966713 |
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name: Cosine Recall@1 |
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- type: cosine_ndcg@10 |
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value: 0.7729838064849864 |
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name: Cosine Ndcg@10 |
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- type: cosine_mrr@1 |
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value: 0.5861241448475948 |
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name: Cosine Mrr@1 |
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- type: cosine_map@100 |
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value: 0.7216697804426214 |
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name: Cosine Map@100 |
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--- |
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# Redis fine-tuned BiEncoder model for semantic caching on LangCache |
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This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) on the [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for sentence pair similarity. |
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## Model Details |
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### Model Description |
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- **Model Type:** Sentence Transformer |
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- **Base model:** [Alibaba-NLP/gte-modernbert-base](https://huggingface.co/Alibaba-NLP/gte-modernbert-base) <!-- at revision e7f32e3c00f91d699e8c43b53106206bcc72bb22 --> |
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- **Maximum Sequence Length:** 100 tokens |
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- **Output Dimensionality:** 768 dimensions |
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- **Similarity Function:** Cosine Similarity |
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- **Training Dataset:** |
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- [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) |
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- **Language:** en |
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- **License:** apache-2.0 |
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### Model Sources |
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- **Documentation:** [Sentence Transformers Documentation](https://sbert.net) |
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- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) |
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- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) |
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### Full Model Architecture |
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``` |
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SentenceTransformer( |
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(0): Transformer({'max_seq_length': 100, 'do_lower_case': False, 'architecture': 'ModernBertModel'}) |
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(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) |
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) |
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``` |
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## Usage |
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### Direct Usage (Sentence Transformers) |
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First install the Sentence Transformers library: |
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```bash |
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pip install -U sentence-transformers |
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``` |
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Then you can load this model and run inference. |
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```python |
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from sentence_transformers import SentenceTransformer |
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# Download from the 🤗 Hub |
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model = SentenceTransformer("redis/langcache-embed-v3") |
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# Run inference |
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sentences = [ |
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'It is known from Australia , including South Australia , Tasmania , Queensland , New South Wales and Victoria .', |
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'It is famous from Australia , including South Australia , Tasmania , Queensland , New South Wales and Victoria .', |
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'In 1792 , the family moved to Kingston in Toronto and then York ( later renamed Upper Canada ) .', |
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] |
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embeddings = model.encode(sentences) |
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print(embeddings.shape) |
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# [3, 768] |
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# Get the similarity scores for the embeddings |
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similarities = model.similarity(embeddings, embeddings) |
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print(similarities) |
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# tensor([[1.0078, 0.9531, 0.5898], |
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# [0.9531, 0.9961, 0.5898], |
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# [0.5898, 0.5898, 0.9922]], dtype=torch.bfloat16) |
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``` |
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<!-- |
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### Direct Usage (Transformers) |
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<details><summary>Click to see the direct usage in Transformers</summary> |
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</details> |
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--> |
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<!-- |
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### Downstream Usage (Sentence Transformers) |
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You can finetune this model on your own dataset. |
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<details><summary>Click to expand</summary> |
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</details> |
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--> |
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<!-- |
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### Out-of-Scope Use |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
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--> |
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## Evaluation |
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### Metrics |
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#### Information Retrieval |
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* Dataset: `test` |
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* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) |
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| Metric | Value | |
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|:-------------------|:----------| |
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| cosine_accuracy@1 | 0.5861 | |
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| cosine_precision@1 | 0.5861 | |
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| cosine_recall@1 | 0.568 | |
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| **cosine_ndcg@10** | **0.773** | |
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| cosine_mrr@1 | 0.5861 | |
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| cosine_map@100 | 0.7217 | |
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<!-- |
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## Bias, Risks and Limitations |
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
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--> |
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<!-- |
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### Recommendations |
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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--> |
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## Training Details |
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### Training Dataset |
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#### LangCache Sentence Pairs (all) |
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* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) |
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* Size: 199 training samples |
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* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code> |
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* Approximate statistics based on the first 199 samples: |
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| | anchor | positive | negative | |
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|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| |
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| type | string | string | string | |
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| details | <ul><li>min: 9 tokens</li><li>mean: 26.47 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 26.47 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 25.93 tokens</li><li>max: 42 tokens</li></ul> | |
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* Samples: |
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| anchor | positive | negative | |
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|:--------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------| |
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| <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>He was at the Westminster School under Richard Busby and studied at Christ Church , Oxford with Henry Aldrich .</code> | |
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| <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>Richard Cheyne was the son and heir of Robert Cralle of Shurland and Margery , daughter and coheiress of Cheyne of Cralle , Sussex .</code> | |
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| <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> | |
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* Loss: <code>losses.AdaFaceInBatchLoss</code> with these parameters: |
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```json |
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{ |
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"scale": 20.0, |
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"similarity_fct": "cos_sim", |
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"gather_across_devices": false |
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} |
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``` |
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### Evaluation Dataset |
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#### LangCache Sentence Pairs (all) |
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* Dataset: [LangCache Sentence Pairs (all)](https://huggingface.co/datasets/redis/langcache-sentencepairs-v2) |
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* Size: 199 evaluation samples |
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* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code> |
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* Approximate statistics based on the first 199 samples: |
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| | anchor | positive | negative | |
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|:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| |
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| type | string | string | string | |
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| details | <ul><li>min: 9 tokens</li><li>mean: 26.47 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 26.47 tokens</li><li>max: 42 tokens</li></ul> | <ul><li>min: 9 tokens</li><li>mean: 25.93 tokens</li><li>max: 42 tokens</li></ul> | |
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* Samples: |
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| anchor | positive | negative | |
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|:--------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------| |
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| <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>He was at the Westminster School under Richard Busby and studied at Christ Church , Oxford with Henry Aldrich .</code> | |
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| <code>The newer punts are still very much in existence today and run in the same fleets as the older boats .</code> | <code>The newer Punts are still very much in existence today and race in the same fleets as the older boats .</code> | <code>Richard Cheyne was the son and heir of Robert Cralle of Shurland and Margery , daughter and coheiress of Cheyne of Cralle , Sussex .</code> | |
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| <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .</code> | <code>Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .</code> | |
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* Loss: <code>losses.AdaFaceInBatchLoss</code> with these parameters: |
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```json |
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{ |
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"scale": 20.0, |
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"similarity_fct": "cos_sim", |
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"gather_across_devices": false |
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} |
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``` |
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### Training Logs |
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| Epoch | Step | test_cosine_ndcg@10 | |
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|:-----:|:----:|:-------------------:| |
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| -1 | -1 | 0.7730 | |
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### Framework Versions |
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- Python: 3.12.3 |
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- Sentence Transformers: 5.1.0 |
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- Transformers: 4.56.0 |
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- PyTorch: 2.8.0+cu128 |
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- Accelerate: 1.10.1 |
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- Datasets: 4.0.0 |
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- Tokenizers: 0.22.0 |
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## Citation |
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### BibTeX |
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#### Sentence Transformers |
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```bibtex |
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@inproceedings{reimers-2019-sentence-bert, |
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title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", |
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author = "Reimers, Nils and Gurevych, Iryna", |
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booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", |
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month = "11", |
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year = "2019", |
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publisher = "Association for Computational Linguistics", |
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url = "https://arxiv.org/abs/1908.10084", |
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} |
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``` |
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## Glossary |
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*Clearly define terms in order to be accessible across audiences.* |
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