---
license: mit
datasets:
- cxllin/economics
- meta-math/MetaMathQA
language:
- en
metrics:
- accuracy
tags:
- finance
- math
- economics
---
![Llama2-7b-economist](https://pbs.twimg.com/media/F9lHLh-XQAAGThI?format=jpg&name=900x900)


# Llama2-7b-economist

Llama2-7b-economist is a state-of-the-art language model with 7 billion parameters, specifically fine-tuned on extensive Macro and Micro Economic theory. It aims to provide data-driven economic insights and predictions.

## Model Details

### Model Description

Llama2-7b-economist represents the intersection of cutting-edge AI modeling and economic theory. By leveraging a vast parameter space and meticulous fine-tuning, this model seeks to transform the way we approach and understand economic data.

- **Developed by:** [Collin Heenan](mailto:cheenan@worcester.edu)
- **Model type:** Transformer-based Language Model
- **Language(s):** English
- **License:** MIT
- **Finetuned from model:** Llama2-7b Base Model

### Model Sources

- **Repository:** [More Information Needed]
- **Demo:** [More Information Needed]

## Uses

### Direct Use

- Economic predictions based on text inputs.
- Answering questions related to Macro and Micro Economic theories.
- Analyzing economic texts and extracting insights.

### Downstream Use

- Potential to be fine-tuned for specific economic tasks, such as economic sentiment analysis or financial forecasting.

### Out-of-Scope Use

- Non-economic related tasks.
- Predictions that require non-textual data, like graphs or charts.

## Bias, Risks, and Limitations

[More Information Needed]

### Recommendations

Users should ensure they are using Llama2-7b-economist in appropriate economic contexts and be cautious of extrapolating predictions without expert validation.

## How to Get Started with the Model

[More Information Needed]

## Training Details

![Llama2-7b-economist](https://cdn.discordapp.com/attachments/1168701768876695603/1168903136484802610/Screenshot_2023-10-28_at_11.05.31_PM.jpg?ex=655374e0&is=6540ffe0&hm=ab54293de359e1bdda4528af070e3561fea79062552b45b988eaf70a19dbdb1d&)


### Training Data

- Comprehensive Macro and Micro Economic theory datasets.

### Training Procedure 

#### Training Hyperparameters

- **Training regime:** Training on 1x t4 GPU

## Evaluation

### Testing Data, Factors & Metrics

#### Testing Data

[More Information Needed]

#### Factors

[More Information Needed]

#### Metrics

[More Information Needed]

### Results

[More Information Needed]

## Environmental Impact

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute).

- **Hardware Type:** NVIDIA T4 GPU
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]

## Technical Specifications

### Model Architecture and Objective

Transformer-based architecture with 7 billion parameters, designed to understand and predict economic patterns and insights.

### Compute Infrastructure

#### Hardware

- 1x t4 GPU

## Contact

- [Collin Heenan](mailto:cheenan@worcester.edu)