Comments (2)
@yuxuan2015 之前我们用OpenAssistant跑过RLHF,这一块如果没有高质量的数据会损害模型的能力。由于单纯用instruction tuning也可以有比较好的对话效果,RLHF的作用更多在于安全生成,惩罚一些难以在代码层面后处理的不良输出,或者是在归一参数这块(比如我们generate的时候有时效果不好需要设置一下)。
如果后续有高质量的数据我们会考虑引入。
from chinese-vicuna.
Reward Model不够好的话会损耗模型性能。这是因为你们用来finetune的数据是OpenAI的经过RLHF等处理后的高质量输出,而OpenAssistant RLHF的数据质量远不如这个,所以起到反作用。如果从零开始研发模型,没有OpenAI的标准答案,那么充分的alignment还是很有意义的。
@yuxuan2015 之前我们用OpenAssistant跑过RLHF,这一块如果没有高质量的数据会损害模型的能力。由于单纯用instruction tuning也可以有比较好的对话效果,RLHF的作用更多在于安全生成,惩罚一些难以在代码层面后处理的不良输出,或者是在归一参数这块(比如我们generate的时候有时效果不好需要设置一下)。
如果后续有高质量的数据我们会考虑引入。
from chinese-vicuna.
Related Issues (20)
- 有办法改成分类任务么,用LlamaForSequenceClassification模型类加载
- transformers和pydantic问题 HOT 1
- 是因为梯度为0吗?
- 多卡finetune_chat时报mat1 and mat2 shapes cannot be multiplied (1024x2 and 1x11008) HOT 2
- 中文乱码 HOT 5
- 请问多个lora模型怎么合并?
- 请问llama7b_4bit_128g的input shape是多少呢 HOT 1
- 运行chat_7B.sh聊两句话out of memory
- 多卡训练 bash scripts/finetune.sh报错 HOT 1
- 这几个不同路径下的模型是否有区别?
- 运行generate脚本之后,在页面提问,很久没有产生回答,后台无报错 HOT 2
- OSError: Not enough disk space. Needed: Unknown size (download: Unknown size, generated: Unknown size, post-processed: Unknown size)
- 从belle+guanaco数据集中抽取前5000条样本训练lora,效果不好
- deepspeed跑模型相关问题
- 使用finetune.sh来指令微调llama-33b,出现ZeroDivisionError: integer division or modulo by zero错误 HOT 2
- 可以提供一下huggingface上的Chinese-Vicuna/llama7b_4bit_128g模型的config.json和tokenizer么?
- 官方colab安裝套件失效
- 如果更改數據集格式,要如何更改代碼
- 可以更新一下requirements吗? HOT 1
- 关于中断训练继续训练。 HOT 16
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from chinese-vicuna.