Overview

DCAgent/a1-stack_dockerfile is an 8 billion parameter language model, derived from the Qwen/Qwen3-8B architecture. It has been specifically fine-tuned on a specialized dataset, /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--exp_rpt_stack-dockerfile_glm_4.7_traces_jupiter/snapshots/59210899ea2276b8151d7228f95052ff85502993_thinking_preprocessed, which suggests a focus on tasks related to Dockerfiles.

Key Characteristics

• Base Model: Qwen/Qwen3-8B
• Parameter Count: 8 billion parameters
• Context Length: 32,768 tokens
• Specialized Training: Fine-tuned on a dataset related to Dockerfile traces, indicating a domain-specific optimization.

Training Details

The model was trained with the following key hyperparameters:

• Learning Rate: 4e-05
• Optimizer: ADAMW_TORCH_FUSED
• Epochs: 7.0
• Batch Size: A total train batch size of 16 across 16 devices.

Potential Use Cases

Given its specialized training, this model is likely best suited for:

• Generating Dockerfiles from natural language descriptions.
• Analyzing and interpreting existing Dockerfile configurations.
• Assisting in debugging or optimizing Dockerfile instructions.
• Automating tasks related to container image creation and management.