Model Overview

This model, shubhamrgandhi/qwen3-8b-full-sft-prm-opus-distill-32k-lr5e6_rejection-sample_think, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has undergone a specific fine-tuning process on the prm_sft_train dataset.

Key Training Details

• Base Model: Qwen/Qwen3-8B
• Fine-tuning Dataset: prm_sft_train
• Context Length: 32,768 tokens
• Learning Rate: 5e-06
• Optimizer: AdamW (betas=(0.9, 0.999), epsilon=1e-08)
• Epochs: 3.0
• Batch Size: 1 (train), 8 (eval) per device, totaling 8 (train) and 64 (eval) across 8 devices.

Intended Use Cases

While specific intended uses and limitations are not detailed in the provided documentation, this model is suitable for tasks that align with the fine-tuning objectives of the prm_sft_train dataset. Developers should evaluate its performance for their specific applications, particularly those benefiting from a Qwen3-8B base with this training configuration.