Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning   Although machine learning models typically experience a drop in performance
on out-of-distribution data, accuracies on in- versus out-of-distribution data
are widely observed to follow a single linear trend when evaluated across a
testbed of models. Models that are more accurate on the out-of-distribution
data relative to this baseline exhibit "effective robustness" and are
exceedingly rare. Identifying such models, and understanding their properties,
is key to improving out-of-distribution performance. We conduct a thorough
empirical investigation of effective robustness during fine-tuning and
surprisingly find that models pre-trained on larger datasets exhibit effective
robustness during training that vanishes at convergence. We study how
properties of the data influence effective robustness, and we show that it
increases with the larger size, more diversity, and higher example difficulty
of the dataset. We also find that models that display effective robustness are
able to correctly classify 10% of the examples that no other current testbed
model gets correct. Finally, we discuss several strategies for scaling
effective robustness to the high-accuracy regime to improve the
out-of-distribution accuracy of state-of-the-art models.

15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin