Ruckus-13b-29 Model Overview

The flytech/Ruckus-13b-29 is a fine-tuned language model based on the Meta Llama-2-13b-hf architecture, indicating a 13 billion parameter count. While specific details about its primary differentiators, intended applications, and the dataset used for fine-tuning are not available in the provided documentation, its foundation suggests general language understanding and generation capabilities.

Training Details

The model underwent training with the following key hyperparameters:

• Learning Rate: 0.0002
• Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
• Epochs: 16
• Batch Size: 32 (for both training and evaluation)
• Scheduler: Constant learning rate scheduler

This training configuration suggests a focus on stable and consistent learning over a moderate number of epochs. The model was developed using Transformers 4.33.3, Pytorch 2.0.1+cu118, Datasets 2.14.5, and Tokenizers 0.13.3.

Limitations

Due to the lack of detailed information regarding the fine-tuning dataset and specific use cases, users should exercise caution and conduct thorough evaluations for any particular application. The model's performance and suitability for specific tasks are currently undefined.