Update README.md

README.md

@@ -4,12 +4,14 @@
 
 ## Model Description
 
-ConceptFrameMet is a state-of-the-art metaphor detection model based on the AdaptiveSourceQAMelBert architecture. It not only detects metaphors but also predicts:
+ConceptFrameMet is a metaphor detection model which not only detects metaphors but also predicts:
 
 1. **Metaphor Classification**: Whether a target word is used metaphorically or literally
 2. **Semantic Frames**: The conceptual frame evoked by the target word
 3. **Source Domains**: The source domain of the metaphor (for metaphorical uses)
 
+Please see https://github.com/julia-nixie/ConceptFrameMet and PAPER LINK for details.
+
 ## Model Architecture
 
 - **Base Model**: RoBERTa-base
@@ -26,10 +28,9 @@ Evaluated on standard metaphor detection benchmarks:
 
 | Dataset | F1 Score | Accuracy |
 |---------|----------|----------|
-| VUA18   | ~0.78    | ~0.82    |
-| VUA20   | ~0.70    | ~0.75    |
-| MOH-X   | ~0.80    | ~0.85    |
-| TroFi   | ~0.63    | ~0.67    |
+| VUA18   | 0.767    | 0.930    |
+| MOH-X   | 0.814    | 0.803    |
+| TroFi   | 0.633    | 0.605    |
 
 ## Quick Start
 
@@ -46,7 +47,7 @@ from transformers import RobertaTokenizer
 import torch
 
 # Load model and tokenizer
-model_path = "YOUR_USERNAME/ConceptFrameMet"
+model_path = "nixie1981/ConceptFrameMet"
 tokenizer = RobertaTokenizer.from_pretrained(model_path)
 
 # Example sentence
@@ -95,22 +96,6 @@ The model returns a dictionary with:
 - `source`: Predicted source domain (for metaphors)
 - `source_confidence`: Confidence for source prediction
 
-## Training Details
-
-- **Training Dataset**: VUA18 (Visual University Amsterdam metaphor corpus)
-- **Epochs**: 20 (with early stopping)
-- **Batch Size**: 32
-- **Learning Rate**: 3e-5
-- **Optimizer**: AdamW
-- **Seed**: 42
-
-## Limitations
-
-1. Performance may vary on domain-specific text
-2. Works best on English text
-3. Requires target word to be specified
-4. Frame and source predictions depend on availability of auxiliary models
-
 ## Citation
 
 If you use this model in your research, please cite:
@@ -124,15 +109,7 @@ If you use this model in your research, please cite:
 }
 ```
 
-## Related Models
-
-- **Base Architecture**: RoBERTa (Liu et al., 2019)
-- **MelBERT**: Choi et al., "MelBERT: Metaphor Detection via Contextualized Late Interaction"
-- **Frame Prediction**: nixie1981/sem_frames
-
-## License
 
-[Specify your license]
 
 ## Contact