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  5. Hard Negative
Training & Fine-tuningaka Hard Negatives

Hard Negative

A hard negative is a wrong example that looks very similar to the correct one, used in contrastive training to force a model to learn fine distinctions.

Ask Melo about this← all terms

Easy negatives are cheap but teach shallow features. Hard negatives, such as a near-miss option or a nearly identical function call with the wrong argument, are mined or synthesized. CLM-8B used 30M synthetic hard negatives in its mid-training stage to separate near-miss actions from correct ones.

Related terms

Contrastive LearningInfoNCE LossEmbeddingContrastive Language ModelEarly StoppingKnowledge Distillation

Where Hard Negative comes up

  • What Is a Contrastive Language Model (CLM)? A Plain Explanation
  • Contrastive Language Model (CLM-8B): An Open System One Model That Matches Jev at Up to 9x Lower Latency