Update linear_benchmark.rst

docs/source/evaluations/linear_benchmark.rst

@@ -2,7 +2,7 @@ Benchmark: Linear Image Classification
 ===========================================================
 
 VISSL provides a standardized benchmark suite to evaluate the feature representation quality of self-supervised pretrained models. A popular
-evaluation protocol is to freeze the model traink and train linear classifiers on several layers of the model on some target datasets (like ImageNet-1k, Places205, VOC07, iNaturalist2018).
+evaluation protocol is to freeze the model trunk and train linear classifiers on several layers of the model on some target datasets (like ImageNet-1k, Places205, VOC07, iNaturalist2018).
 In VISSL, we support linear evaluations on all the common datasets. We also provide standard set of hyperparams for various approaches
 in order to reproduce the model performance in SSL literature. For reproducibility, see `VISSL Model Zoo <https://github.com/facebookresearch/vissl/blob/main/MODEL_ZOO.md>`_.