Update README.md

README.md

@@ -11,12 +11,12 @@ configs:
 This is the benchmark for CI builds repair task as part of the
 🏟️ [Long Code Arena benchmark](https://huggingface.co/spaces/JetBrains-Research/long-code-arena).
 
-> 🛠️ CI build repair: given the logs of a failed GitHub Actions workflow and the corresponding repository shapshot, fix the
+> 🛠️ CI build repair: given the logs of a failed GitHub Actions workflow and the corresponding repository shapshot, repair the
 > repository contents in order to make the workflow pass.
 
 All the data is collected from repositories published under permissive licenses (MIT, Apache-2.0, BSD-3-Clause, and BSD-2-Clause). The datapoints can be removed upon request.
 
-To score your model on this dataset, you can use [**CI build repair benchmark**](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark).
+To score your model on this dataset, you can use [**CI build repair benchmark**](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-builds-repair/ci-builds-repair-benchmark).
 
 ## How-to
 
@@ -32,7 +32,7 @@ To score your model on this dataset, you can use [**CI build repair benchmark**]
     ```
     from datasets import load_dataset
 
-    dataset = load_dataset("JetBrains-Research/lca-ci-fixing", split="test")
+    dataset = load_dataset("JetBrains-Research/lca-ci-builds-repair", split="test")
     ```
 
    Note that all the data we have is considered to be in the test split.  
@@ -46,11 +46,9 @@ followed by the commit that passes the workflow successfully.
 
 Note that, unlike other 🏟️ Long Code Arena datasets, this dataset does not contain repositories.
 
-* Our [CI builds repair benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark) clones the necessary repos to the user's local machine. The user should run
-  their model to
-  fix the failing CI workflows, and the benchmark will push commits to GitHub, returning the results of the workflow
-  runs
-  for all the datapoints.
+* Our [CI builds repair benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-builds-repair/ci-builds-repair-benchmark) clones the necessary repos to the user's local machine. 
+  The user should run their model to repair the failing CI workflows, and the benchmark will push commits to GitHub,
+  returning the results of the workflow runs for all the datapoints.
 
 ### Datapoint Schema
 
@@ -60,7 +58,7 @@ Each example has the following fields:
 | Field               | Description                                                                                                                  |
 |---------------------|------------------------------------------------------------------------------------------------------------------------------|
 | `contributor`       | Username of the contributor that committed changes                                                                           |
-| `difficulty`        | Difficulty of the problem (assessor-based. 0 means that the fix requires only the code formatting)                                                                                   |
+| `difficulty`        | Difficulty of the problem (assessor-based. 1 means that the repair requires only the code formatting)                                                                                   |
 | `diff`              | Contents of the diff between the failed and the successful commits                                                           |
 | `head_branch`       | Name of the original branch that the commit was pushed at                                                                    |
 | `id`                | Unique ID of the datapoint                                                                                                   |
@@ -83,7 +81,7 @@ Each example has the following fields:
 ```
 {'contributor': 'Gallaecio',
  'diff': 'diff --git a/scrapy/crawler.py b/scrapy/crawler.py/n<...>',
- 'difficulty': '1',
+ 'difficulty': '2',
  'head_branch': 'component-getters',
  'id': 18,
  'language': 'Python',