Model Overview

The xiaolesu/OsmosisProofling-v3-SFT is an 8 billion parameter instruction-tuned model, built upon the robust Qwen/Qwen3-8B architecture. It has been specifically fine-tuned using the xiaolesu/OsmosisProofling-v3-SFT dataset, indicating a specialization towards the characteristics and tasks present in this dataset.

Key Training Details

• Base Model: Qwen/Qwen3-8B
• Fine-tuning Dataset: xiaolesu/OsmosisProofling-v3-SFT
• Training Framework: Axolotl (version 0.16.0.dev0)
• Context Length: Configured for a sequence length of 4096 tokens during training.
• Optimization: Utilizes adamw_torch_fused optimizer with a learning rate of 1e-05 and a cosine learning rate scheduler.
• Memory Footprint: Achieved a maximum active memory of 20.98 GiB during evaluation.

Performance Metrics

During evaluation, the model achieved notable results:

• Validation Loss: 0.3543
• Perplexity (PPL): 1.4252

Intended Uses & Limitations

While specific intended uses and limitations are not detailed in the provided information, the model's fine-tuning on a particular dataset suggests its strengths lie in tasks similar to those within the xiaolesu/OsmosisProofling-v3-SFT dataset. Users should evaluate its performance on their specific use cases, especially considering the specialized nature of its training.