Datasets:

hobbesthecomputerscientist
/

mock-trial-datav2

dataset_info:
  features:
    - name: text
      dtype: string
  splits:
    - name: train
      num_bytes: 77039
      num_examples: 51
  download_size: 33828
  dataset_size: 77039
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: mit
task_categories:
  - text-generation
language:
  - en
tags:
  - legal
  - mock-trial
  - experimental
  - prompt-engineering

Mock-Trial-Data-v2 (Experimental)

This is the second-generation training set for the Mock Trial AI project. It represents an intensive experimental phase focused on testing various prompt architectures and instruction-following capabilities for legal simulations.

🧪 The Research Phase

While v3 is the current production standard, v2 was the laboratory where the core logic was forged. This dataset contains the 51 initial instruction-response pairs used to identify the optimal "Loss Floor" for Llama 3.1 8B fine-tuning.

👉 Looking for the latest? Check out v3 Data here

Dataset Description

Curated by: HobbesTheComputerScientist
Focus: Prompt Engineering & Instruction Adherence
Format: Instruction-Response pairs (JSONL)

Experimental Scope

In this version, I heavily experimented with Prompt Permutations to see which linguistic structures most effectively reduced model hallucination during witness cross-examination. Key experiments included:

Constraint Density: Testing how many rules of evidence could be packed into a single instruction before reasoning degraded.
Persona Persistence: Testing variations in deponent background descriptions to prevent the model from "breaking character."
Negative Constraint Testing: Training the model specifically on what not to say (e.g., avoiding legal conclusions).

Lessons Learned (The Bridge to V3)

The 51 examples in this set revealed that:

Over-constraining the prompt increased the loss by making the model too "robotic."
The model needed more specific "Objection/Response" pairs to handle courtroom interruptions.
These insights led directly to the Instruction Distillation methodology used in the current V3 Production Space.

Licensing

Distributed under the MIT License. For educational use in mock trial and legal-tech research.