jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452
The jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452 is an 8 billion parameter language model, fine-tuned from Qwen/Qwen3-8B-Base. It was specifically trained on the Anthropic/hh-rlhf dataset, aiming to enhance helpfulness and reduce harmfulness in responses. This model is optimized for generating helpful and safe text, making it suitable for applications requiring aligned conversational AI.
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Overview
This model, jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452, is an 8 billion parameter language model derived from the Qwen3-8B-Base architecture. It has undergone supervised fine-tuning (SFT) using the Anthropic/hh-rlhf dataset, which is designed to improve model helpfulness and harmlessness.
Training Details
The fine-tuning process involved specific hyperparameters:
- Learning Rate: 2e-05
- Batch Size: 8 (train), 8 (eval)
- Gradient Accumulation: 2 steps, leading to a total effective batch size of 64
- Optimizer: AdamW with betas=(0.9, 0.999)
- Scheduler: Cosine learning rate scheduler with 0.1 warmup ratio
- Epochs: 1
During training, the model achieved a validation loss of 1.3682, indicating its performance on the alignment task. The training utilized a multi-GPU setup with 4 devices.
Intended Use Cases
This model is primarily intended for applications where generating helpful and safe responses is critical. Its fine-tuning on the Anthropic/hh-rlhf dataset suggests suitability for:
- Aligned conversational agents
- Customer support chatbots
- Content generation requiring ethical guidelines
Limitations
As with any fine-tuned model, its performance is directly influenced by the training data. Further evaluation is recommended for specific deployment scenarios to understand its full capabilities and potential biases.