DCAgent/g1_gptlong_top8_8b
DCAgent/g1_gptlong_top8_8b is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. This model is specifically adapted for long context understanding and generation, leveraging a specialized dataset for its training. It is designed for applications requiring robust performance over extended conversational or textual inputs.
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Model Overview
DCAgent/g1_gptlong_top8_8b is an 8 billion parameter language model, fine-tuned from the Qwen/Qwen3-8B architecture. This model has been specifically adapted through fine-tuning on the /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--g1_min_episodes_e1_gpt_long_top8_glm47_traces dataset, indicating an optimization for tasks involving extended context lengths or complex multi-turn interactions.
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
- Batch Size: A total training batch size of 96 was achieved using a
train_batch_sizeof 1 andgradient_accumulation_stepsof 2 across 48 devices.
Intended Use Cases
While specific intended uses are not detailed in the provided README, the fine-tuning on a "gpt_long_top8" dataset suggests its suitability for applications that benefit from processing and generating content within a 32K context window. This could include:
- Long-form content generation: Summarizing or creating extensive documents.
- Complex dialogue systems: Maintaining coherence and context over many turns.
- Code analysis or generation: Handling larger codebases or detailed specifications.
- Advanced reasoning tasks: Where understanding intricate relationships across a broad text is crucial.