laion/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_learning-rate_1e-06_Qwen3-32B
The laion/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_learning-rate_1e-06_Qwen3-32B model is a 32 billion parameter language model fine-tuned from Qwen/Qwen3-32B. It was specifically trained on the penfever/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning dataset, suggesting an optimization for reasoning tasks within StackExchange and Overflow sandbox contexts. This model is designed for applications requiring nuanced understanding and generation of content related to technical Q&A forums, leveraging its 32768 token context length.
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Model Overview
This model, laion/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_learning-rate_1e-06_Qwen3-32B, is a specialized fine-tuned version of the Qwen/Qwen3-32B base model. It features 32 billion parameters and supports a substantial context length of 32768 tokens, making it suitable for processing extensive inputs.
Key Specialization
The model's primary differentiation comes from its fine-tuning on the penfever/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning dataset. This training regimen indicates a focus on:
- Reasoning tasks: Optimized for understanding and generating logical responses.
- Technical Q&A: Tailored for content found in StackExchange and similar overflow sandbox environments.
Training Details
Training involved a learning rate of 1e-06, a total batch size of 32 (with 2 gradient accumulation steps), and utilized the AdamW_TORCH_FUSED optimizer. The process ran for 6 epochs, employing a cosine learning rate scheduler with a 0.1 warmup ratio. This configuration aims to enhance the model's performance on its specific fine-tuning domain.