Update README.md

README.md

@@ -7,12 +7,11 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # pull_request_comments_model
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+## Model description
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on a pull request comments dataset.
 It achieves the following results on the evaluation set:
 - Train Loss: 0.0791
 - Train Accuracy: 0.9955
@@ -20,23 +19,26 @@ It achieves the following results on the evaluation set:
 - Validation Accuracy: 0.8291
 - Epoch: 12
 
-## Model description
+## Training and evaluation data
 
-More information needed
+Training and evaluation data used for this model are the pull request comments of the tensorflow repository on GitHub.
+In particular, of all the pull request data (commit comments, review comments, events, exc.) only the rows with Type equal to PC (Pull request Comment) or RC (Review Comment) have been entered into the dataset.
+These comments has been classified into 4 categories:
+1) ML (Machine Learning), if the comment is about specific machine learning aspects, algorithms exc.
+2) Code, if the comment concerns either style and documentation in the code or maintainability issues or possible bugs exc.
+3) Management, if the comment is about management activities like checking an activity status, assign a review to someone, trigger Jenkins CI
+4) Other, if the comment doesn't belong to any of the above categories
 
 ## Intended uses & limitations
 
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+One possible use of this model could be to label the pull request comments, clearly only on GitHub repositories that are about Machine Learning.
+In this way a developer, before reading a comment entirely, can have a preview of what that comment is about.
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
+- batch_size: 32
+- num_epochs: 20
 - optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 280, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
 - training_precision: float32