CLIPood: Generalizing CLIP to Out-of-Distributions
Authors: Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long
ICML 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on diverse datasets with different OOD scenarios show that CLIPood consistently outperforms existing generalization techniques. |
| Researcher Affiliation | Collaboration | 1School of Software, BNRist, Tsinghua University. 2Institute for Interdisciplinary Information Sciences, Tsinghua University. 3Tencent Inc, China. |
| Pseudocode | Yes | Algorithm 1 Training Procedure of CLIPood |
| Open Source Code | Yes | Code is available at https://github.com/thuml/CLIPood. |
| Open Datasets | Yes | We use five multi-domain datasets in Domain Bed (Gulrajani & Lopez-Paz, 2021): PACS (Li et al., 2017), VLCS (Torralba & Efros, 2011), Office Home (Venkateswara et al., 2017), Terra Incognita (Beery et al., 2018) and Domain Net (Peng et al., 2019). |
| Dataset Splits | Yes | We follow the train-validate-test split of each dataset as the Domain Bed benchmark and the leave-one-out evaluation protocol, where at each time, one domain is chosen as the test domain for evaluating OOD generalization, and other domains are chosen as the training domains. |
| Hardware Specification | Yes | We use a machine with 32 CPUs, 256 GB memory, and the NVIDIA TITAN X GPU. |
| Software Dependencies | Yes | For the experiments, we use Py Torch 1.13.1, torchvision 0.14.1, and CUDA 11.6 libraries. |
| Experiment Setup | Yes | We keep the temperature of the softmax function the same as the pre-trained model as τ = 0.01, and use the same hyper-parameter λ = 0.3 for all datasets to avoid over-tuning on specific tasks. We adopt a batch size of 36. We use the Adam W (Loshchilov & Hutter, 2019) optimizer with the cosine learning rate strategy for all datasets. By default, we set β = 0.5, use a learning rate of 5 10 6, and train for 5000 iterations. |