Update README.md

README.md

@@ -11,6 +11,11 @@ metrics:
 model-index:
 - name: PHR_Suicide_Prediction_Roberta_Cleaned
   results: []
+datasets:
+- vibhorag101/suicide_prediction_dataset_phr
+language:
+- en
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,8 +23,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 # PHR_Suicide_Prediction_Roberta_Cleaned
 
-This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
-It achieves the following results on the evaluation set:
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on a Suicide Prediction dataset sourced from Reddit. 
+It achieves the following results on the evaluation/validation set:
 - Loss: 0.1543
 - Accuracy: {'accuracy': 0.9652972367116438}
 - Recall: {'recall': 0.966571403827834}
@@ -30,13 +35,10 @@ It achieves the following results on the evaluation set:
 
 More information needed
 
-## Intended uses & limitations
-
-More information needed
-
 ## Training and evaluation data
-
-More information needed
+The dataset is sourced from Reddit and is available on [Kaggle](https://www.kaggle.com/datasets/nikhileswarkomati/suicide-watch).  
+The dataset contains text with binary labels for suicide or non-suicide.    
+The evaluation set had ~23000 samples, while the training set had ~186k samples, i.e. 80:10:10 (train:test:val) split.    
 
 ## Training procedure
 
@@ -96,4 +98,4 @@ The following hyperparameters were used during training:
 - Transformers 4.31.0
 - Pytorch 2.1.0+cu121
 - Datasets 2.14.5
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3