From afe0c9d1e24b13f231bc662419d1dae03ddfd62b Mon Sep 17 00:00:00 2001
From: pollfly <75068813+pollfly@users.noreply.github.com>
Date: Sun, 8 Aug 2021 15:08:40 +0300
Subject: [PATCH] fix dataset name (#30)

---
 .../pytorch/notebooks/image/image_classification_CIFAR10.md     | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md b/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
index 3c7a10f1..2abc263d 100644
--- a/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
+++ b/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
@@ -4,7 +4,7 @@ title: Image Classification - Jupyter Notebook
 
 The example [image_classification_CIFAR10.ipynb](https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.ipynb) 
 demonstrates integrating **ClearML** into a Jupyter Notebook, which uses PyTorch, TensorBoard, and TorchVision to train a 
-neural network on the UrbanSound8K dataset for image classification. **ClearML** automatically logs the example script's 
+neural network on the CIFAR10 dataset for image classification. **ClearML** automatically logs the example script's 
 calls to TensorBoard methods in training and testing which report scalars and image debug samples, as well as the model 
 and console log. In the example, we also demonstrate connecting parameters to a Task and logging them. When the script runs, 
 it creates an experiment named `image_classification_CIFAR10` which is associated with the `Image Example` project.