---
library_name: transformers
tags:
- trl
- sft
- qna
- jordan-belfort
- sales
- mindset
- persuasion
base_model:
- openchat/openchat_3.5
pipeline_tag: text-generation
---

# Model Card for Jordan Belfort Q&A Model

This model is a fine-tuned version of a transformer-based language model trained using supervised fine-tuning (SFT) on a custom Q&A dataset derived from Jordan Belfort's book. The model is optimized to answer questions related to the book's content, including topics like sales, persuasion, mindset, and personal development strategies.

---

## Model Details

- **Developed by:** Jobix.ai
- **Finetuned from model:** `openchat 3.5*
- **Language(s):** English
- **Model type:** Q&A / Instruction-following
- **License:** apache-2.0 *(or your chosen license)*

---

## Model Sources

- **Training Data:** Custom Q&A dataset built from the full content of Jordan Belfort’s book.
- **Method:** Supervised fine-tuning (TRL + SFT)

---

## Uses

### Direct Use
- Ask specific questions about concepts, strategies, and advice in Jordan Belfort's book.
- Get summaries of chapters, sales techniques, or mindset frameworks presented in the book.
- Useful for salespeople, coaches, or individuals studying persuasion and personal development.

### Out-of-Scope Use
- Not trained for general-purpose Q&A outside the context of the book.
- Not suitable for legal, financial, or medical advice.

---

## Training Details

### Training Procedure
- **Trainer:** `trl.SFTTrainer`
- **Precision:** bfloat16
- **Epochs:** 7
- **Optimizer:** AdamW
- **LR Scheduler:** Cosine with warmup
- **Loss:** CrossEntropyLoss on prompt-response pairs

### Dataset
- Approx. ~2,000 curated Q&A pairs covering all chapters and sections of the book.
- Balanced across concepts like tonality, straight-line persuasion, mindset, sales process, and personal stories.

---

## Evaluation

- Manual evaluation on question coverage and accuracy.
- Model shows strong performance in recalling specific ideas and quoting relevant sections.

---

## Example Usage

```python
from transformers import pipeline

qa = pipeline("text-generation", model="your-username/jordan-belfort-qa")

prompt = "What is the straight-line sales method according to Jordan Belfort?"
response = qa(prompt, max_new_tokens=200, do_sample=False)
print(response[0]["generated_text"])