Merge pull request #765 from iterative/jorgeorpinel

tutorials: metrics.json -> metrics.csv

static/docs/tutorials/versioning.md

@@ -136,7 +136,7 @@ cache.
 Next, we train our first model with `train.py`. Because of the small dataset,
 this training process should be small enough to run on most computers in a
 reasonable amount of time (a few minutes). This command <abbr>outputs</abbr> a
-bunch of files, among them `model.h5` and `metrics.json`, weights of the trained
+bunch of files, among them `model.h5` and `metrics.csv`, weights of the trained
 model, and [metrics](/doc/command-reference/metrics) history. The simplest way
 to capture the current version of the model is to use `dvc add` again:
 
@@ -151,7 +151,7 @@ $ dvc add model.h5
 Let's commit the current state:
 
 ```dvc
-$ git add .gitignore model.h5.dvc data.dvc metrics.json
+$ git add .gitignore model.h5.dvc data.dvc metrics.csv
 $ git commit -m "First model, trained with 1000 images"
 $ git tag -a "v1.0" -m "model v1.0, 1000 images"
 ```
@@ -231,7 +231,7 @@ $ dvc add model.h5
 Let's commit the second version:
 
 ```dvc
-$ git add model.h5.dvc data.dvc metrics.json
+$ git add model.h5.dvc data.dvc metrics.csv
 $ git commit -m "Second model, trained with 2000 images"
 $ git tag -a "v2.0" -m "model v2.0, 2000 images"
 ```
@@ -301,7 +301,7 @@ above (with cats and dogs images) is a good example.
 On the other hand, there are files that are the result of running some code. In
 our example, `train.py` produces binary files (e.g.
 `bottlneck_features_train.npy`), the model file `model.h5`, and the
-[metrics](/doc/command-reference/metrics) file `metrics.json`.
+[metrics](/doc/command-reference/metrics) file `metrics.csv`.
 
 When you have a script that takes some data as an input and produces other data
 <abbr>outputs</abbr>, a better way to capture them is to use `dvc run`:
@@ -319,7 +319,7 @@ When you have a script that takes some data as an input and produces other data
 $ dvc remove -pf model.h5.dvc
 $ dvc run -f Dvcfile \
           -d train.py -d data \
-          -M metrics.json \
+          -M metrics.csv \
           -o model.h5 -o bottleneck_features_train.npy -o bottleneck_features_validation.npy \
           python train.py
 ```
@@ -368,7 +368,7 @@ hands-on experience with pipelines, and try to apply it here. Don't hesitate to
 join our [community](/chat) and ask any questions!
 
 Another detail we only brushed upon here is the way we captured the
-`metrics.json` metrics file with the `-M` option of `dvc run`. Marking this
+`metrics.csv` metrics file with the `-M` option of `dvc run`. Marking this
 <abbr>output</abbr> as a metric enables us to compare its values across Git tags
 or branches (for example, representing different experiments). See `dvc metrics`
 and [Compare Experiments](/doc/get-started/compare-experiments) to learn more