Model Overview

The nandansarkar/qwen3_0-6B_adversarial_4 is a 0.8 billion parameter language model, fine-tuned from a prior iteration, qwen3_0-6B_adversarial_3. This model's development focused on training with adversarial_dataset_4, indicating an emphasis on improving its performance or resilience in adversarial scenarios.

Training Details

The model underwent a single epoch of training with a learning rate of 1e-05. Key hyperparameters included:

• Learning Rate: 1e-05
• Batch Size: 2 (train), 8 (eval)
• Gradient Accumulation Steps: 8
• Optimizer: AdamW with default betas and epsilon
• LR Scheduler: Cosine with 0.05 warmup ratio

Intended Use Cases

Given its adversarial training, this model is likely suitable for:

• Research into model robustness and security.
• Generating or detecting adversarial examples.
• Applications requiring a model with enhanced understanding or resistance to manipulated inputs.