laion/exp-syh-r2egym-askllm-constrained_glm_4_7_traces_jupiter_cleaned
The laion/exp-syh-r2egym-askllm-constrained_glm_4_7_traces_jupiter_cleaned model is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. This model was trained on the /data/cat/ws/befe330h-befe330h-otagent/huggingface/hub/datasets--DCAgent--exp-syh-r2egym-askllm-constrained_glm_4.7_traces_jupiter_cleaned/snapshots/d13cd4ded646d8380dc70005a25fadeae9836514_thinking_preprocessed dataset. Its specific differentiators and primary use cases are not detailed in the provided information, suggesting it may be an experimental or specialized fine-tune.
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Overview
This model, exp-syh-r2egym-askllm-constrained_glm_4_7_traces_jupiter_cleaned, is an 8 billion parameter language model based on the Qwen3-8B architecture. It has been fine-tuned on a specific dataset located at /data/cat/ws/befe330h-befe330h-otagent/huggingface/hub/datasets--DCAgent--exp-syh-r2egym-askllm-constrained_glm_4.7_traces_jupiter_cleaned/snapshots/d13cd4ded646d8380dc70005a25fadeae9836514_thinking_preprocessed.
Training Details
The fine-tuning process involved:
- Learning Rate: 4e-05
- Batch Size: 1 (train), 8 (eval)
- Gradient Accumulation: 2 steps, resulting in a total train batch size of 16
- Optimizer: ADAMW_TORCH_FUSED with betas=(0.9, 0.98) and epsilon=1e-08
- Scheduler: Cosine learning rate scheduler with a 0.1 warmup ratio
- Epochs: 7.0
Limitations
The model card indicates that more information is needed regarding its specific intended uses, limitations, and training/evaluation data. Developers should exercise caution and conduct thorough testing to determine its suitability for particular applications, as its unique capabilities or optimizations are not explicitly defined.