diff --git a/docs/user-guide/tutorials/evaluate_resnet.md b/docs/user-guide/tutorials/evaluate_resnet.md index 4f66068f..ef5b2a77 100644 --- a/docs/user-guide/tutorials/evaluate_resnet.md +++ b/docs/user-guide/tutorials/evaluate_resnet.md @@ -21,18 +21,18 @@ Now let's adapt the new `bach.yaml`-config to the new model: path: timm.create_model arguments: model_name: resnet18 - num_classes: &NUM_CLASSES 2 + num_classes: &NUM_CLASSES 4 drop_rate: 0.0 pretrained: false ``` -To reduce training time, lets overwrite some of the default parameters. In the terminal where you run ***eva***, set: +To reduce training time, lets overwrite some of the default parameters. In the terminal where you run *eva*, set: ``` export OUTPUT_ROOT=logs/resnet/bach -export MAX_STEPS=20 -export LR_VALUE=0.1 +export MAX_STEPS=50 +export LR_VALUE=0.01 ``` Now train and evaluate the model by running: ``` eva fit --config configs/vision/resnet18/bach.yaml ``` -Once the run is complete, take a look at the results in `logs/resnet/bach//results.json`. How does the performance compare to the results observed in the previous tutorials? +Once the run is complete, take a look at the results in `logs/resnet/bach//results.json` and check out the tensorboard with `tensorboard --logdir logs/resnet/bach`. How does the performance compare to the results observed in the previous tutorials?