LoRA setup:

  • Rank: 256
  • Alpha: 512
  • Target modules: ["up_proj", "down_proj", "gate_proj", "o_proj"]

Training:

  • 1 Epoch
  • Learning rate: 8e-4
  • LR scheduler: Cosine
  • Warmup ratio: 0.05
  • Batch size: 1
  • 4 A100 (40GB) GPUs
  • Gradient accumulation steps: 64
  • Effective batch size: 256
  • Max. context length: 8192 tokens

(renamed from jekunz/smollm-135m-lora-fineweb-fao-test3)

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