Model Overview

ShenaoZ/0.000001_ablation_iter_2 is a 7 billion parameter language model, representing a fine-tuned iteration of its predecessor, ShenaoZ/0.000001_ablation_iter_1. This model was developed by ShenaoZ, focusing on iterative refinement based on updated and original datasets.

Training Details

The model underwent a single training epoch with a learning rate of 5e-08, utilizing an Adam optimizer with betas=(0.9, 0.999) and epsilon=1e-08. Training was conducted on 8 multi-GPU devices with a total batch size of 128, employing a cosine learning rate scheduler with a warmup ratio of 0.1. The training process used Transformers 4.36.2, Pytorch 2.1.2+cu121, Datasets 2.14.6, and Tokenizers 0.15.2.

Intended Use

Given its nature as an "ablation iteration," this model is primarily suited for research and experimental purposes. It is designed for developers and researchers to investigate the impact of specific changes or dataset updates on model performance, rather than for general-purpose deployment. Its iterative development suggests a focus on understanding model behavior and optimization strategies.