jtatman/Reyna-Mini-1.8B-v0.2-function-call-laser is a 1.8 billion parameter model, fine-tuned by jtatman using the LaserRMT technique on Aloobun's Reyna-Mini-1.8B-v0.2 base model. This model is optimized for conversational text generation and chat applications, with an experimental function-calling capability. Its primary differentiator is the use of LaserRMT for refining weights, aiming for improved conversational fluency in a compact size.
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Model Overview
This model, developed by jtatman, is a LaserRMT fine-tuned version of Aloobun's Reyna-Mini-1.8B-v0.2. It focuses on enhancing conversational abilities and introduces experimental function-calling features. The fine-tuning process utilized the LaserRMT technique, which refines model weights by focusing on the highest-scored weights based on noise-to-ratio analysis, aiming to improve performance while slightly reducing model size.
Key Capabilities
- Conversational AI: Designed for engaging chat and general text generation.
- Function Calling: Includes experimental function-calling capabilities, with plans for future improvements.
- Efficient Fine-tuning: Leverages the LaserRMT technique to avoid training low-performing weights, contributing to a more efficient and potentially smaller model.
Training Details
The model was trained using Axolotl for training and dataset tokenization. The dataset was formatted in ShareGpt conversational style. Hyperparameters included lora_r: 64, lora_alpha: 16, num_epochs: 3, and learning_rate: 0.00025. Evaluation metrics show varying performance across benchmarks like TruthfulQA, Winogrande, and MMLU, with an MMLU accuracy of 0.2533.