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Note: This checkpoint is from a single random seed (seed=3) and a specific training step (step 4220). Results may vary across seeds.
| Key | Value |
|---|---|
| Base model | meta-llama/Llama-2-7b-hf |
| Task | MMLU |
| Data selection | Full SFT (BM25) |
| Data ratio | 100% |
| Online | False |
| LoRA rank | 128 |
| LoRA alpha | 512 |
| Target modules | q_proj, k_proj, v_proj, o_proj |
| Seed | 3 |
| Checkpoint step | 4220 |
1from peft import PeftModel
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf")
5model = PeftModel.from_pretrained(base_model, "DATA-ADAPT/full-sft")
6tokenizer = AutoTokenizer.from_pretrained("DATA-ADAPT/full-sft")