Update README.md

README.md

@@ -19,6 +19,8 @@ metrics:
 - macro-f1
 
 ---
+# Note
+This model is training with 180k+ ABSA samples, see [ABSADatasets](https://github.com/yangheng95/ABSADatasets). Yet the test sets are not included in pre-training, so you can use this model for training and benchmarking on common ABSA datasets, e.g., Laptop14, Rest14 datasets. (Except for the Rest15 dataset!)
 
 # DeBERTa for aspect-based sentiment analysis
 The `deberta-v3-base-absa` model for aspect-based sentiment analysis, trained with English datasets from [ABSADatasets](https://github.com/yangheng95/ABSADatasets).
@@ -39,9 +41,9 @@ outputs = model(**inputs)
 ```
 
 ## Example in PyASBA
-An [example](https://github.com/yangheng95/PyABSA/blob/release/demos/aspect_polarity_classification/train_apc_multilingual.py) for using FAST-LCF-BERT in PyASBA
+An [example](https://github.com/yangheng95/PyABSA/blob/release/demos/aspect_polarity_classification/train_apc_multilingual.py) for using FAST-LCF-BERT in PyASBA datasets.
 
-## Datasets
+## Datasets 
 This model is fine-tuned with 180k examples for the ABSA dataset (including augmented data). Training dataset files:
 ```
 loading: integrated_datasets/apc_datasets/SemEval/laptop14/Laptops_Train.xml.seg