Update README.md

README.md

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 ## Overview
 This BERT-based text classifier was developed as a thesis project for the Computer Engineering degree at Universidad de Buenos Aires (UBA). 
 The model is designed to detect sentiments in Spanish and was fine-tuned on the *dccuchile/bert-base-spanish-wwm-uncased* model using a specific set of hyperparameters. 
-It was trained on a dataset containing 11,500 Spanish tweets collected from various regions, both positive and negative.
+It was trained on a dataset containing 11,500 Spanish tweets collected from various regions, both positive and negative. This model was trained using a well-curated combination of datasets from TASS.
+
 
 ## Team Members
 - **[Azul Fuentes](https://github.com/azu26)**
@@ -48,8 +49,6 @@ The model's performance was evaluated using the following metrics:
   * **Precision = _86.46%_**
   * **Recall = _86.51%_**
 
-    
-
 ## Usage
 ### Installation
 You can install the required dependencies using pip:
@@ -92,7 +91,8 @@ print(f"Probabilities: {probabilities}")
 ```
 
 ## License
-Apache License 2.0
+* Apache License 2.0
+* [TASS Dataset license](http://tass.sepln.org/tass_data/download.php)
 
 ## Acknowledgments
 Special thanks to DCC UChile for the base Spanish BERT model and to all contributors to the dataset used for training.