Update README.md

README.md

@@ -4,6 +4,10 @@ license: mit
 base_model: FacebookAI/roberta-base
 tags:
 - generated_from_trainer
+- debagreement
+- stance
+- debate
+- disagreement
 metrics:
 - accuracy
 - f1
@@ -25,17 +29,23 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended for detecting stance (agreement, disagreement, neutrality) in Reddit comment reply pairs. It was trained on political subreddit data from the DEBAGREEMENT dataset and may not generalize well to other domains or platforms.
 
 ## Training and evaluation data
 
-More information needed
-
-## Training procedure
+- **Base model**: [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) (125M parameters)
+- **Dataset**: [Jiyog/debagreement-cp](https://huggingface.co/datasets/Jiyog/debagreement-cp) (DEBAGREEMENT)
+- **Task**: 3-class sequence classification (sentence-pair input)
+- **Input format**: `body_parent` (premise) + `body_child` (hypothesis)
+- **Epochs**: 3
+- **Batch size**: 16
+- **Max sequence length**: 512 tokens
+- **Optimizer**: AdamW (default HuggingFace Trainer)
+- **Weight decay**: 0.01
+- **Best model selected by**: Weighted F1
 
 ### Training hyperparameters
 
@@ -63,4 +73,4 @@ The following hyperparameters were used during training:
 - Transformers 5.0.0
 - Pytorch 2.10.0+cu128
 - Datasets 4.0.0
-- Tokenizers 0.22.2
+- Tokenizers 0.22.2