| --- |
| language: |
| - en |
| license: llama4 |
| library_name: peft |
| pipeline_tag: text-generation |
| base_model: meta-llama/Llama-4-Scout-17B-16E-Instruct |
| datasets: |
| - itsalloverig/adaption-indian-legal-triage-samples-v4 |
| tags: |
| - legal |
| - india |
| - indian-law |
| - adaption |
| - autoscientist |
| - instruction-tuning |
| - lora |
| - legal-research |
| model_name: MIKE |
| --- |
| |
| # MIKE |
|
|
| MIKE is an India-focused legal research and triage adapter trained through |
| Adaption AutoScientist on top of |
| `meta-llama/Llama-4-Scout-17B-16E-Instruct`. |
|
|
| The model helps legal teams classify issues, identify missing facts and |
| documents, plan research, handle source-grounded questions, and flag |
| uncertainty. It is not a substitute for advice from a qualified Indian legal |
| professional. |
|
|
| ## Release status |
|
|
| This repository contains the selected MIKE v4 controlled-fused LoRA adapter, |
| which achieved a 92.16% Adaption held-out pairwise score. The adapter, |
| tokenizer, and configuration files are included. |
|
|
| Access to the gated Meta Llama 4 Scout base model is required to load the |
| adapter. The adapter configuration references the official base repository. |
|
|
| ## Selected training run |
|
|
| - Adaption dataset ID: `9b5b4f7d-f099-450e-a6b6-7c185864eacd` |
| - Source corpus: 12,673 rows |
| - Platform train/validation/test rows: 7,172 / 228 / 236 |
| - Fine-tune job: `6fd6244e-46b6-46dc-93ec-97de856291ce` |
| - AutoScientist experiment: `8d2362dd-51d6-4445-b88f-62664090e3fe` |
| - Provider job: `ft-31293977-6cb2` |
| - Base model: `meta-llama/Llama-4-Scout-17B-16E-Instruct` |
| - Training method: instruction SFT with LoRA |
| - Prompt/completion contract: `rephrased_prompt` to `fused_generation` |
| - Epochs: 4 |
| - LoRA rank/alpha/dropout: 64 / 128 / 0 |
| - Learning rate: 1e-4 |
| - Scheduler: cosine |
|
|
| ## Evaluation |
|
|
| The selected run received an Adaption in-house pairwise score of **92.16%** |
| against the Llama 4 Scout base model: |
|
|
| - fine-tuned-model wins: 210 |
| - base-model wins: 11 |
| - ties: 15 |
| - prompts: 236 |
| - judge: `google/gemini-3.1-pro-preview` |
| - judge failures: 0 |
| - generation failures: 0 |
|
|
| The score gives half credit to ties: |
|
|
| `(210 + 0.5 * 15) / 236 = 0.9216` |
|
|
| This is a pairwise preference score, not a claim that the model is 92.16% |
| factually accurate. A separate 100-case Indian-law domain evaluation scored |
| 65.66% (56 fine-tuned wins, 25 base wins, 18 ties, one judge failure). |
|
|
| ## Intended uses |
|
|
| - preliminary Indian legal issue triage; |
| - research planning and document collection; |
| - source-bounded statutory or judgment-excerpt analysis; |
| - uncertainty and unsupported-citation detection; |
| - legacy/current criminal-law transition screening involving IPC/CrPC/IEA and |
| BNS/BNSS/BSA. |
|
|
| ## Out-of-scope uses |
|
|
| - final legal advice or representation; |
| - predicting guaranteed outcomes; |
| - filing without professional review; |
| - generating allegations or authorities unsupported by supplied facts and |
| sources; |
| - use outside India without separate adaptation and evaluation. |
|
|
| ## Limitations |
|
|
| - Legal rules and procedural requirements change over time. |
| - A plausible answer can still be incorrect or incomplete. |
| - The 12,673-row controlled corpus preserves all 10,913 high-signal v2 rows, |
| adds 860 quality-gated recovery examples, and adds 900 explicit |
| no-unprovided-authority variants. |
| - Server-side previews found that some fused targets are overly long and may |
| introduce assumptions or unnecessary authority references. |
| - Independent qualified Indian legal review and current official-source |
| grounding remain required. |
|
|
| ## License |
|
|
| The adapter is distributed under the Llama 4 Community License because it is |
| a derivative of Llama 4. Users must also comply with Meta's Acceptable Use |
| Policy and the base model's access requirements. See `NOTICE` and |
| https://www.llama.com/llama4/license/. |
|
|
| The associated dataset is licensed separately in its |
| [public dataset repository](https://huggingface.co/datasets/itsalloverig/adaption-indian-legal-triage-samples-v4). |
|
|
| ## Acknowledgements |
|
|
| Built with Adaption Adaptive Data and AutoScientist for the Legal track of the |
| Adaption AutoScientist Challenge x HackIndia. |
|
|
