llama2-13b-fintune2

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在llama-2-13b上使用huangyt/FINETUNE2資料集進行訓練，採用與platypus相近參數

Fine-Tuning Information

• GPU: RTX4090 (single core / 24564MiB)
• base model: meta-llama/Llama-2-13b-hf
• dataset: huangyt/FINETUNE2 (共約3w筆訓練集)
• peft_type: LoRA
• lora_rank: 16
• lora alpha: 8
• lora dropout: 0.05
• lora_target: gate_proj, up_proj, down_proj
• per_device_train_batch_size: 8
• gradient_accumulation_steps: 8
• learning_rate : 4e-4
• epoch: 1
• batch size: 8
• microbatch size: 4
• warmup steps: 100
• weight decay: cosine
• cutoff length: 2048
• precision: bf16
• group_by_length: True
• load_in_8bit: True

Fine-Tuning Detail

• train_loss: 0.0823
• train_runtime: 02:40:01

Evaluation

• 評估結果來自HuggingFaceH4/open_llm_leaderboard
• 與Llama-2-13b比較4種Benchmark，包含ARC、HellaSwag、MMLU、TruthfulQA