Overview

This model, exp_tas_max_episodes_32_traces, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has undergone fine-tuning on the DCAgent/exp_tas_max_episodes_32_traces dataset, indicating a specialization towards the characteristics and patterns present in this particular data. The training process involved a learning rate of 4e-05, a total batch size of 16 (with gradient accumulation steps of 2), and was conducted over 7 epochs using a cosine learning rate scheduler.

Key Training Details

• Base Model: Qwen/Qwen3-8B
• Fine-tuning Dataset: DCAgent/exp_tas_max_episodes_32_traces
• Learning Rate: 4e-05
• Optimizer: ADAMW_TORCH_FUSED
• Epochs: 7.0
• Context Length: 32768 tokens

Intended Use

While specific intended uses and limitations require further information, the model's fine-tuning suggests its application would be most effective in scenarios closely aligned with the data it was trained on. Developers should consider the nature of the DCAgent/exp_tas_max_episodes_32_traces dataset to determine suitability for their specific tasks.