Model Overview

DCAgent/b1_top4_seq is an 8 billion parameter language model, fine-tuned from the robust Qwen/Qwen3-8B base model. It was trained on the /scratch/08134/negin/hub/datasets--DCAgent--b1_top4_seq/snapshots/01924f6f86b8e836e06754caadf99b88aa4cbcb4 dataset, suggesting a specialization in tasks related to sequential data processing.

Key Training Details

• Base Model: Qwen/Qwen3-8B
• Learning Rate: 4e-05
• Optimizer: ADAMW_TORCH_FUSED with betas=(0.9, 0.98) and epsilon=1e-08
• Epochs: 7.0
• Distributed Training: Multi-GPU setup with 16 devices, resulting in a total training batch size of 16.

Intended Use Cases

While specific intended uses and limitations are not detailed in the provided information, its fine-tuning on a sequential dataset implies potential strengths in:

• Processing and generating sequential data.
• Tasks requiring understanding of ordered information.

Users should conduct further evaluation to determine its suitability for specific applications, especially given the general nature of the provided model description.