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版本資訊

使用新的噪聲較小(理論上)的數據訓練
Lora使用了更大的r(32)
取消了Dora
因為Dora的提升有限,還會大幅降低訓練和推理的效率

簡介

Riyuechang/Breeze-7B-PTT-Chat-v2所使用的,未與主模型MediaTek-Research/Breeze-7B-Instruct-v1_0合併的lora模型

設備

  • Ubuntu 22.04.4 LTS
  • NVIDIA GeForce RTX 3060 12G

Lora參數

r=32,
lora_alpha=32,
lora_dropout=0.1,
task_type="CAUSAL_LM",
target_modules="all-linear",
bias="none",
use_rslora=True

訓練參數

per_device_train_batch_size=28,  
gradient_accumulation_steps=1,  
num_train_epochs=3,  
warmup_ratio=0.1,  
learning_rate=2e-5,  
bf16=True,  
save_strategy="steps",  
save_steps=1000,  
save_total_limit=5,  
logging_steps=10,  
output_dir=log_output,  
optim="paged_adamw_8bit",  
gradient_checkpointing=True

結果

  • loss: 0.9391
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