Model Overview

ShinjiCodeEVA/student_feedback_v1_Qwen3-4B-Base is a 4 billion parameter language model, finetuned from the unsloth/Qwen3-4B-Base architecture. Developed by ShinjiCodeEVA, this model leverages the Qwen3 base for its core capabilities.

Key Characteristics

• Base Model: Qwen3-4B-Base, providing a robust foundation for language tasks.
• Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
• Context Length: Supports a context length of 32768 tokens, allowing for processing of substantial input texts.

Potential Use Cases

This model is specifically designed for applications involving student feedback, likely excelling in tasks such as:

• Analyzing and summarizing student comments.
• Generating structured feedback based on raw input.
• Assisting in the categorization or sentiment analysis of educational responses.

Licensing

The model is released under the Apache-2.0 license, allowing for broad use and distribution.