laion/GLM-4_7-r2egym_sandboxes-maxeps-131k
The laion/GLM-4_7-r2egym_sandboxes-maxeps-131k model is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B. It is specifically adapted using the DCAgent2/GLM-4.7-r2egym_sandboxes-maxeps-131k dataset. This model is optimized for tasks related to the r2egym sandboxes environment, suggesting a specialization in reinforcement learning or agent-based interactions within simulated environments.
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Model Overview
This model, laion/GLM-4_7-r2egym_sandboxes-maxeps-131k, is an 8 billion parameter language model derived from the Qwen3-8B architecture. It has been fine-tuned on the DCAgent2/GLM-4.7-r2egym_sandboxes-maxeps-131k dataset, indicating a specialized application rather than a general-purpose LLM.
Training Details
The fine-tuning process involved specific hyperparameters:
- Learning Rate: 4e-05
- Batch Size: 1 (train), 8 (eval)
- Gradient Accumulation: 2 steps, resulting in a total effective batch size of 16
- Optimizer: ADAMW_TORCH_FUSED with betas=(0.9, 0.98) and epsilon=1e-08
- LR Scheduler: Cosine type with a warmup ratio of 0.1
- Epochs: 7.0
Potential Use Cases
Given its fine-tuning dataset, this model is likely intended for tasks within simulated environments, particularly those related to r2egym sandboxes. This suggests applications in:
- Agent behavior generation
- Reinforcement learning environments
- Simulated interaction analysis
Limitations
The model card indicates that more information is needed regarding its specific intended uses, limitations, and detailed training/evaluation data. Users should exercise caution and conduct thorough testing for their specific applications.