DCAgent/g1_original_1k_8b
DCAgent/g1_original_1k_8b is an 8 billion parameter language model fine-tuned from Qwen/Qwen3-8B. This model is specifically trained on a dataset derived from 'g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_traces_1k', indicating a specialization in processing and generating content related to specific trace data. Its 32K context length supports handling extensive input sequences for detailed analysis or generation tasks.
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DCAgent/g1_original_1k_8b Overview
DCAgent/g1_original_1k_8b is an 8 billion parameter language model, fine-tuned from the base Qwen/Qwen3-8B architecture. This model has undergone specialized training on a unique dataset, /e/scratch/jureap59/raoof1/sft_data/hf_hub/datasets--DCAgent--g1_min_episodes_e1_gpt_long_d1_original_40k_glm47_traces_1k/snapshots/09c22b498460fd0ed83413eec6dbf62be30d205a_thinking_preprocessed, which suggests a focus on processing and understanding specific types of trace or episode data.
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
Potential Use Cases
Given its specialized fine-tuning, this model is likely best suited for applications requiring:
- Analysis of specific trace data: Processing and interpreting the kind of 'g1_min_episodes' and 'glm47_traces' data it was trained on.
- Contextual understanding: Leveraging its 32K context length for tasks that require deep comprehension of long, detailed sequences related to its training domain.
Further details on specific capabilities, intended uses, and limitations would require more information from the model developers.