DCAgent/g1_timeout_e1_gpt_long_tacc
DCAgent/g1_timeout_e1_gpt_long_tacc is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. It was trained on the DCAgent/g1_timeout_e1_gpt_long_d1_original_40k_glm47_traces dataset, suggesting specialization in specific agentic or long-context tasks. With a context length of 32768 tokens, this model is likely optimized for processing and generating extended sequences of text relevant to its training data.
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Model Overview
This model, DCAgent/g1_timeout_e1_gpt_long_tacc, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has been specifically fine-tuned on the DCAgent/g1_timeout_e1_gpt_long_d1_original_40k_glm47_traces dataset, indicating a potential specialization in tasks related to agentic behavior, long-context understanding, or specific trace analysis.
Key Training Details
The fine-tuning process utilized a learning rate of 4e-05 and was conducted over 7.0 epochs. Training involved 16 distributed devices, resulting in a total batch size of 16. The optimizer used was ADAMW_TORCH_FUSED with standard beta values and an epsilon of 1e-08, employing a cosine learning rate scheduler with a 0.1 warmup ratio.
Potential Use Cases
Given its fine-tuning dataset, this model is likely best suited for applications requiring:
- Processing and generating long sequences of text.
- Tasks related to agentic systems or trace analysis.
- Scenarios where understanding extended context is crucial.