Model Overview

This model, exp_tas_max_episodes_512_traces, is an 8 billion parameter language model derived from the Qwen/Qwen3-8B architecture. It has undergone a specific fine-tuning process using the DCAgent/exp_tas_max_episodes_512_traces dataset.

Training Details

The fine-tuning process involved several key hyperparameters:

• Learning Rate: 4e-05
• Batch Size: 1 (train), 8 (eval)
• Gradient Accumulation: 2 steps, leading to a total effective batch size of 16
• Optimizer: AdamW (fused) with betas=(0.9, 0.98) and epsilon=1e-08
• LR Scheduler: Cosine with a 0.1 warmup ratio
• Epochs: 7.0
• Devices: Trained across 8 GPUs

Potential Use Cases

Given its fine-tuning on a dataset related to 'exp_tas_max_episodes_512_traces', this model is likely specialized for tasks involving:

• Analysis of agent trajectories or sequences of actions.
• Understanding and generating responses within environments characterized by episodes and traces.
• Applications requiring a nuanced interpretation of sequential data, potentially in reinforcement learning or simulation contexts.

Limitations

As per the provided information, specific details regarding intended uses, limitations, and comprehensive training/evaluation data are not fully documented. Users should conduct thorough testing for their specific applications.