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1)跑通广告数据集的代码; 2)运行自己数据集; 3)发现破坏原有结构的,即问些普通的问题,回答错误; 4)issues 里有人说是--learning_rate 1e-4,太大了,要改为--learning_rate 1e-5,运行3万epoch; 5)已运行了3万次,确实没有破坏结构,但还是达不到训练集的效果,比如在1.5万次时,可以做到“question:哪个组适用于小于13kg的婴儿床的组。 answer:适用于小于13kg的婴儿床的组是A组。”,训练集为“适用于小于13kg的婴儿床的组是C组。”,之后的1.5万次,很难训练成功。其他的问答集也如此。
No response
请问有什么方法,让大模型拟合问答集。
- OS: - Python: - Transformers: - PyTorch: - CUDA Support (`python -c "import torch; print(torch.cuda.is_available())"`) :
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Current Behavior
1)跑通广告数据集的代码;
2)运行自己数据集;
3)发现破坏原有结构的,即问些普通的问题,回答错误;
4)issues 里有人说是--learning_rate 1e-4,太大了,要改为--learning_rate 1e-5,运行3万epoch;
5)已运行了3万次,确实没有破坏结构,但还是达不到训练集的效果,比如在1.5万次时,可以做到“question:哪个组适用于小于13kg的婴儿床的组。 answer:适用于小于13kg的婴儿床的组是A组。”,训练集为“适用于小于13kg的婴儿床的组是C组。”,之后的1.5万次,很难训练成功。其他的问答集也如此。
Expected Behavior
No response
Steps To Reproduce
请问有什么方法,让大模型拟合问答集。
Environment
Anything else?
No response
The text was updated successfully, but these errors were encountered: