Update README.md

README.md

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 ---
-license: apache-2.0
+license: other
+language:
+- en
+pipeline_tag: sentence-similarity
+datasets:
+- sentence-transformers/msmarco-msmarco-distilbert-base-v3
+- microsoft/ms_marco
 ---
+
+# constructai/taylor-v1-128-emb
+
+This model is a fine-tuned version of a custom BERT-like encoder (hidden_size=384, 6 layers) trained on MS MARCO passage ranking dataset.  
+It uses **triplet hard negatives** from [`sentence-transformers/msmarco-msmarco-distilbert-base-v3`](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3) (Apache-2.0 license). The base MS MARCO data is subject to [Microsoft Research License](https://github.com/microsoft/MSMARCO-Passage-Ranking/blob/master/LICENSE).
+
+The model produces **384-dimensional** embeddings (CLS token) optimized for cosine similarity.
+
+# Training details
+
+* Max sequence length: 128 tokens
+
+* Loss: MultipleNegativesSymmetricRankingLoss (InfoNCE)
+
+* Batch size: 128 (32 + gradient accumulation)
+
+* Learning rate: 2e-5
+
+* Data: ~500k triplets from MS MARCO
+
+# Evaluation
+
+On a small test set, the model achieves:
+
+* Positive pair similarity: 0.58
+
+* Negative pair similarity: 0.14
+
+* Margin: 0.44
+
+#