Update README with complete metadata and citations

README.md

@@ -59,7 +59,6 @@ pip install torch transformers
 ```python
 import torch
 from transformers import AutoTokenizer
-from huggingface_hub import PyTorchModelHubMixin
 
 # Load model and tokenizer
 model_name = "fffffwl/swe-cefr-sp"
@@ -69,11 +68,6 @@ from convert_proto_model_to_hf import CEFRPrototypeModel
 model = CEFRPrototypeModel.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
-# Or download the checkpoint and use it directly:
-# checkpoint = torch.hub.load_state_dict_from_url(
-#     f"https://huggingface.co/{model_name}/resolve/main/model.safetensors"
-# )
-
 # Example text
 text = "Jag heter Anna och jag kommer från Sverige."
 
@@ -125,6 +119,14 @@ class CEFRPrototypeModel(PreTrainedModel):
         pass
 ```
 
+## Performance
+
+On the Swedish CEFR sentence dataset (10k sentences from COCTAILL, 8 Sidor, and SUC3):
+
+- **Macro-F1**: 84.1%
+- **Quadratic Weighted Kappa (QWK)**: 94.6%
+- **Accuracy**: Significantly outperforms BERT baseline by 12.1% in macro-F1
+
 ## Training Details
 
 ### Dataset
@@ -157,23 +159,53 @@ class CEFRPrototypeModel(PreTrainedModel):
 If you use this model in your research, please cite:
 
 ```bibtex
-@inproceedings{fan2024swecefrsp,
-  title={Swedish CEFR Level Estimation with Prototype-based Models},
-  author={Your Name},
-  year={2024}
+@misc{fan2024swedish,
+  title={Swedish Sentence-Level CEFR Classification with LLM Annotations},
+  author={Fan, Wenlin},
+  year={2024},
+  howpublished={\url{https://huggingface.co/fffffwl/swe-cefr-sp}}
 }
 ```
 
+Or as part of the broader project:
+
+```bibtex
+@misc{fan2024swecefrsp,
+  title={Swedish CEFR Sentence-level Assessment using Large Language Models},
+  author={Fan, Wenlin},
+  year={2024},
+  publisher={GitHub},
+  howpublished={\url{https://github.com/fanwenlin/swe-cefr-sp}},
+  note={Dataset, LLM annotating codes and sentence-level assessment codes available}
+}
+```
+
+## Project Links
+
+- **GitHub Repository**: https://github.com/fanwenlin/swe-cefr-sp
+- **Hugging Face Space**: Available with interactive demo
+- **Dataset**: 10k Swedish sentences annotated from COCTAILL, 8 Sidor, and SUC3
+- **Main Model**: This prototype-based model (k=3) with Swedish BERT
+
+## Related Work
+
+This work builds upon:
+- Yoshioka et al. (2022): CEFR-based Sentence Profile (CEFR-SP) and prototype-based metric learning
+- Volodina et al. (2016): Swedish passage readability assessment
+- Scarton et al. (2018): Controllable text simplification
+
 ## License
 
 This model is released under the MIT License. See LICENSE file for details.
 
 ## Related Models
 
+This repository also contains:
 - Original k=1 checkpoint: `metric-proto-k1.pt`
 - Original k=3 checkpoint: `metric-proto-k3.pt` (this model)
 - Original k=5 checkpoint: `metric-proto-k5.pt`
 - BERT baseline: `bert-baseline.pt`
 - Megatron version: `metric-proto-megatron-k3.pt`
+- Traditional ML models: `linear_regression.joblib`, `logreg.joblib`, `svm.joblib`, `mlp.joblib`, `tree.joblib`
 
 For more details, visit the [project repository](https://github.com/fanwenlin/swe-cefr-sp).