lora info

README.md

@@ -18,25 +18,31 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-large-uncased-swag
 
-This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
+This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on [SWAG](https://huggingface.co/datasets/allenai/swag) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.4643
 - Accuracy: 0.8295
 
 ## Model description
 
-More information needed
+
 
 ## Intended uses & limitations
 
-More information needed
+This model should be used as an expert in the [Meteor-of-LoRA framework](https://github.com/ParagonLight/meteor-of-lora).
 
 ## Training and evaluation data
 
-More information needed
+The data were splitted based on HuggingFace default dataset:
+
+```python3
+dataset = load_dataset("swag")
+```
 
 ## Training procedure
 
+Our approach focuses explicitly on adapting the Transformers weights' Wq (query) and Wv (value) in the attention module for parameter efficiency.
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: