DAPT(domain-adaptive pretraining):在目标领域的数据上做预训练。 TAPT(task-adaptive pretraining):在具体任务的无标签数据上做训练。 整个预训练的流程为 Broad-domain -> domain-specific -> task-specific 最终提升效果还是比较明显的。 Hybrid approaches ...
为了在有效成本情况下训练特定领域(domain-specific)模型,论文提出结合以下技术:使用领域适应( domainadapted)的tokenizers对基础模型进行领域自适应预训练(Domain-Adaptive PreTraining,DAPT),使用通用和特定领域指令进行模型对齐,以及使用训练好的领域适应检索模型进行检索增强生成(retrieval-augmented generation,RAG)。 如图1...
During Domain-Adaptive Pre-Training (DAPT), we assemble a dataset from a combination of NVIDIA-proprietary chip design specific data sources and publicly available datasets. Chip Design Datasets:Our internal dataset consists of a diverse range of text sources pertinent to chip design, spanning design...
In this section we present detailed results on our domain adaptive pretrained models. We also detail our ablation experiments on domain adaptive pretraining. DAPT Hyperparameters:Details presented in Table VI. TABLE VI: DAPT and SFT hyperparameters, SFT values shown in parenthesis (if differs from...
2.1 Domain-adaptive pretraining Encoders pretrained using general-domain corpus may not serve as appropriate encoders for domain-specific tasks. To adapt the encoder to the target domain in the pretraining phase, DAPT has been conducted in several major domains that differs a lot from the general...
Domain-Adaptive Pre-Training (DAPT) Configurations --train_data_file:The file path of the pre-training corpus. --output_dir:The output directory where the pre-trained model is saved. --model_name_or_path:Continue pre-training on which model. ...
A domain‐adapted encoder is tailored for equipment fault NER through domain‐adaptive pretraining (DAPT). Update of word segmentation dictionary and adjustment of masking approach are implemented during DAPT for information enrichment, which helps make the most of the limited domain‐specific pre...
We apply the aforementioned two baseline models for fine-tuning our home decoration domain dataset. To explore the advantages of domain-adaptive pretraining(DAPT)[Gururangan et al., 2020]in domain adaptation, we will conduct identical instruction tuning experiments on models refined using DAPT. ...
pre-training on large-scale generative models under three different settings: 1) source domain pre-training; 2) domain-adaptive pre-training; and 3) task-adaptive pre-training. Experiments show that the effectiveness of pre-training is correlated with the similarity between the pre-training data ...
Recently, domain-specific PLMs have been proposed to boost the task performance of specific domains (e.g., biomedical and computer science) by continuing to pre-train general PLMs with domain-specific corpora. However, this Domain-Adaptive Pre-Training (DAPT; Gururangan et al. (2020)) tends ...