Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,5 @@
+{
+    "embedding_dimension": 768,
+    "pooling_mode": "mean",
+    "include_prompt": true
+}

README.md

@@ -0,0 +1,109 @@
+---
+language:
+  - en
+  - ms
+tags:
+  - sentence-transformers
+  - embedding
+  - retrieval
+  - rag
+  - malaysian
+  - manglish
+  - multilingual
+license: mit
+model_type: sentence-transformers
+base_model: paraphrase-multilingual-mpnet-base-v2
+---
+
+# Aranda-v1
+
+Aranda-v1 is a sentence embedding model specialized for **Malaysian text retrieval**, including Bahasa Malaysia, Manglish (Malaysian English code-switching), and cross-lingual BM↔English matching. It outperforms the base model on all retrieval metrics across all four language categories.
+
+## Training
+
+Two-phase contrastive curriculum:
+
+**Phase 1 — Breadth:** MultipleNegativesRankingLoss on 1M Malaysian positive pairs (paraphrases, social media, news, QA). LR=1e-5, 1000 steps.
+
+**Phase 2 — Discrimination:** Fine-tuned on 58K diverse hard-negative triplets (Lowyat, Twitter, Facebook, formal BM QA, English anchors, cross-lingual pairs) with explicit mined hard negatives. LR=2e-6, 2000 steps.
+
+Base model: `paraphrase-multilingual-mpnet-base-v2`
+
+## Evaluation
+
+Tested on 4,149 retrieval queries (BM, Manglish, English, Cross-lingual) with ~25 candidates per query.
+
+### Overall Retrieval
+
+| Model | Recall@1 | Recall@5 | Recall@10 | MRR |
+|---|---:|---:|---:|---:|
+| mpnet-base | 0.8631 | 0.9937 | 0.9973 | 0.9200 |
+| multilingual-e5-base | 0.8470 | 0.9940 | 0.9988 | 0.9091 |
+| **Aranda-v1** | **0.8891** | **0.9961** | **0.9998** | **0.9364** |
+
+### Per-Language Recall@1
+
+| Model | BM | Manglish | English | Cross-lingual |
+|---|---:|---:|---:|---:|
+| mpnet-base | 0.8200 | 0.8988 | 0.8577 | 0.8267 |
+| **Aranda-v1** | **0.8431** | **0.9290** | **0.8792** | **0.8500** |
+
+### Additional Metrics
+
+| Metric | mpnet-base | Aranda-v1 |
+|---|---:|---:|
+| Mesolitica NDCG@10 | 0.4699 | **0.4706** |
+| English STS Spearman | **0.8682** | 0.8369 |
+| Manglish Heuristic Spearman | 0.3937 | **0.4536** |
+
+## Usage
+
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("rekabytes/Aranda-v1")
+
+# Encode texts
+embeddings = model.encode([
+    "macam mana nak renew lesen memandu",
+    "how to renew driving license",
+    "saya nak makan nasi lemak"
+], normalize_embeddings=True)
+
+# Cosine similarity
+similarities = embeddings @ embeddings.T
+print(similarities)
+```
+
+### With RAG / vector search
+
+```python
+# Encode your document corpus (do this once)
+doc_embeddings = model.encode(documents, normalize_embeddings=True)
+
+# At query time
+query_embedding = model.encode([query], normalize_embeddings=True)
+scores = query_embedding @ doc_embeddings.T
+top_k = scores.argsort()[0][-5:][::-1]
+```
+
+## Intended Use
+
+- **RAG context retrieval** for Malaysian applications
+- **Semantic search** over BM/Manglish/English document corpora
+- **Cross-lingual matching** (BM ↔ English)
+- **Dense retrieval** in hybrid search pipelines (paired with BM25)
+
+## Limitations
+
+- English STS performance is below the base model (0.8369 vs 0.8682) — the model specialized for Malaysian text
+- Not a reranker — use a cross-encoder for second-stage reranking
+- Tested on Malaysian web data; performance may vary on other Southeast Asian languages
+
+## Model Details
+
+- **Architecture:** XLM-RoBERTa (base)
+- **Embedding dimension:** 768
+- **Max sequence length:** 128
+- **Pooling:** Mean
+- **Normalization:** L2

config.json

@@ -0,0 +1,31 @@
+{
+  "add_cross_attention": false,
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.12.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "__version__": {
+    "pytorch": "2.7.0+cu128",
+    "sentence_transformers": "5.6.0",
+    "transformers": "5.12.1"
+  },
+  "default_prompt_name": null,
+  "model_type": "SentenceTransformer",
+  "prompts": {
+    "document": "",
+    "query": ""
+  },
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9223161ac53fb61da63546d63c8ae3ce8f474c968ed24ea8914b05ae7916070a
+size 1112197096

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "feature-extraction",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "last_hidden_state"
+        }
+    },
+    "module_output_name": "token_embeddings"
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cad551d5600a84242d0973327029452a1e3672ba6313c2a3c3d69c4310e12719
+size 17082987

tokenizer_config.json

@@ -0,0 +1,22 @@
+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "is_local": true,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 128,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}