88 + super(DPO_Loss, self).__init__() 89 + self.config = config 90 + self.reference_free = self.config.reference_free 91 + self.logsigmoid = nn.LogSigmoid() 92 + self.sigmoid = nn.Sigmoid() 93 + self.loss_type = self.config.loss_type 94 + self.label_smoothing = ...
您好,感谢如此优秀的框架,我在进行单机8卡, dpo训练时, 当开启ring-attention时, loss与未开启该配置时diff较大, 且ring-attn-size越大, loss震荡幅度越大, 如下图, 蓝色是未开启ring-attn的曲线, 红色是ring-attn-size=2, 灰色是ring-attn-size=8;
DPO 的损失函数是通过对比偏好数据对中的评分差来进行优化的,其目标是使模型能够更准确地区分偏好对中的优劣选项。#大语言模型 #大模型 #模型训练 #预训练模型 #大规模预训练模型 #算法 #面试问题 发布于 2024-10-26 22:49・IP 属地上海 赞同19 分享收藏 写下你的评论... 1 条评论 ...
online 生成数据后用rm打分+dpo loss成为了一个常见选择,那么在这基础上还能咋玩?这论文,除了rm作为ranker引导DPO loss外,每隔一段时间就去收集一部分人类数据作为金标,更新RM + DPO 训练。直觉上,金标的单独训练能够引导出真偏好出来,然后RM再做进一步泛化引导。
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The DPO model is trained with the following config: Training Parameters: Epochs: 1 Batch Size: 1 Gradient Accumulation Steps: 2 Learning Rate: 1e-7 Learning Rate Decay: Cosine Weight Decay: 1e-2 DPO Loss Parameter: Beta: 0.1 Useful Links TitleLinkDescription DPO paper PDF The original pap...
evaluate_dpo_loss_loader#336 New issue Closed #337Description nerdai opened on Feb 23, 2025 No description provided. Activity Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees nerdai LabelsNo labels Projects llms-from-scratch Status ...
Reminder I have read the README and searched the existing issues. System Info 8XH100 Reproduction 更新到master分支的最新的transformer & trl库,DPO训练LOSS从之前的1.0->0.3 变为9->3 详情见huggingface/transformers#34191 Expected behavior No response Others
I want to optimize an LLM based on DPO. When I tried to train and evaluate the model, but there are nan values in the evaluation results. import torch from transformers import AutoModelForCausalLM, AutoTokenizer from datasets import Data...
Why do I encounter 'loss': 0.0, 'grad_norm': tensor(nan, device='cuda:0', dtype=torch.float64) when fine-tuning llava-v1.5-7b using the dpo code from the llava-next repository? Below is my training script, and I have ensured that my training dataset is fine. ...