---
license: apache-2.0
library_name: transformers
base_model: google/gemma-3-270m-it
tags:
- gemma
- finance
- lora
- unsloth
- text-generation
- instruction-following
datasets:
- gbharti/finance-alpaca
- Balaji173/finance_news_sentiment
- winddude/reddit_finance_43_250k
- causal-lm/finance
pipeline_tag: text-generation
language:
- en
---

# Gemma-3 Finance Mix

A lightweight **Gemma-3 270M** model fine-tuned for *financial Q&A, causal-lm/finance, news-headline sentiment and retail-investor discourse*.

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## Overview

| Item | Details |
|---|---|
| **Base checkpoint** | `google/gemma-3-270m-it` |
| **Fine-tune method** | LoRA (PEFT) with Unsloth|
| **Training run** | 1 epoch • 325,528 blended examples • 100 steps |
| **Trainable params** | 30.4 M / 298 M (10.18 %) |
| **Loss** | 4.11 → **2.74** |
| **Hardware** | 2 × T4-16GB (Collab Free Tier) |
| **License** | Apache-2.0 |
| **Intended use** | Educational & research

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## Datasets

| Dataset | Size | Focus |
|---|---|---|
| `gbharti/finance-alpaca` | 52 k | Instruction Q-A on corporate finance & investing |
| `Balaji173/finance_news_sentiment` | 217 k | Bullish/bearish labels for news headlines |
| `winddude/reddit_finance_43_250k` | 250 k | Reddit finance post–comment pairs |
| `causal-lm/finance` | 31 k | Analytical prompts & causal reasoning in economics/markets |

All shards were concatenated and wrapped with the **Gemma chat template** before training.

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## Responsible use

Disclose AI assistance, double-check outputs, and do **not** rely on this model for trading decisions. The author and base-model creators accept no liability for financial losses.

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