seandearnaley/llama3-8b-sentiment-may-22-2024-2epoches
seandearnaley/llama3-8b-sentiment-may-22-2024-2epoches is a Llama 3 8B instruction-tuned model developed by seandearnaley, fine-tuned using Unsloth and Huggingface's TRL library. This model is specifically optimized for sentiment analysis, particularly focusing on text related to potential future stock values of companies. It is designed to output sentiment analysis results in a structured JSON format, making it suitable for automated financial text processing.
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Model Overview
This model, seandearnaley/llama3-8b-sentiment-may-22-2024-2epoches, is a specialized Llama 3 8B instruction-tuned model developed by seandearnaley. It was fine-tuned using the Unsloth library, which enabled faster training, and Huggingface's TRL library.
Key Capabilities
- Sentiment Analysis: Primarily designed to analyze the sentiment of text, with a specific focus on financial implications, such as the potential future stock value of mentioned companies.
- Structured Output: Configured to respond with sentiment analysis results in a JSON format, facilitating integration into automated workflows.
- Optimized Training: Leverages Unsloth for efficient and accelerated fine-tuning.
Use Cases
This model is particularly well-suited for:
- Financial Sentiment Analysis: Analyzing news articles, social media, or reports to gauge market sentiment towards specific companies or stocks.
- Automated Trading Signals: Generating sentiment scores that can be used as input for algorithmic trading strategies.
- Market Research: Providing insights into public perception and sentiment trends affecting financial markets.
For more details on its development and application, refer to the accompanying article: Elevating Sentiment Analysis @Medium.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.