Upload EVA Lender Matching adapter (SFT + DPO trained)

README.md

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+---
+license: apache-2.0
+base_model: mlx-community/Llama-3.2-3B-Instruct-4bit
+tags:
+  - finance
+  - lender-matching
+  - mlx
+  - lora
+  - dpo
+  - sba-loans
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# EVA Lender Matching Model
+
+Fine-tuned Llama 3.2 3B model for SBA lender matching and financial advisory.
+
+## Model Description
+
+This model was trained using:
+- **SFT (Supervised Fine-Tuning)**: 500 iterations on lender matching data
+- **DPO (Direct Preference Optimization)**: 500 iterations for preference alignment
+
+### Training Results
+| Stage | Initial Loss | Final Loss | Improvement |
+|-------|-------------|------------|-------------|
+| Val Loss | 2.902 | 0.331 | 88.6% reduction |
+| Train Loss | 2.495 | 0.300 | 88.0% reduction |
+
+## Usage
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load(
+    "mlx-community/Llama-3.2-3B-Instruct-4bit",
+    adapter_path="evafiai/eva-lender-matching"
+)
+
+prompt = "I need a $500,000 SBA loan for my manufacturing business. What lenders do you recommend?"
+response = generate(model, tokenizer, prompt=prompt, max_tokens=300)
+print(response)
+```
+
+## Capabilities
+
+- SBA 7(a) and 504 loan recommendations
+- Lender matching based on business profile
+- NAICS code identification
+- Industry-specific financing guidance
+
+## Training Data
+
+Trained on:
+- 7,393 preference pairs for DPO
+- Comprehensive lender database with verified contacts
+- NAICS code matching examples
+
+## License
+
+Apache 2.0

adapter_config.json

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+{
+    "adapter_path": "eva_dpo_training_live/adapters",
+    "batch_size": 1,
+    "config": null,
+    "data": "eva_dpo_mlx_format",
+    "fine_tune_type": "lora",
+    "grad_accumulation_steps": 1,
+    "grad_checkpoint": true,
+    "iters": 500,
+    "learning_rate": 3e-06,
+    "lora_parameters": {
+        "rank": 8,
+        "dropout": 0.0,
+        "scale": 20.0
+    },
+    "lr_schedule": null,
+    "mask_prompt": false,
+    "max_seq_length": 2048,
+    "model": "mlx-community/Llama-3.2-3B-Instruct-4bit",
+    "num_layers": 16,
+    "optimizer": "adam",
+    "optimizer_config": {
+        "adam": {},
+        "adamw": {},
+        "muon": {},
+        "sgd": {},
+        "adafactor": {}
+    },
+    "project_name": null,
+    "report_to": null,
+    "resume_adapter_file": "eva_lender_FIXED_20251128_155922/adapters/adapters.safetensors",
+    "save_every": 100,
+    "seed": 0,
+    "steps_per_eval": 100,
+    "steps_per_report": 25,
+    "test": false,
+    "test_batches": 500,
+    "train": true,
+    "val_batches": 25
+}

adapters.safetensors

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+oid sha256:3607bc6f1c2c9443f23508b1f39770d771eecdb57dc7cee60db1e3d26df470ae
+size 27811400