Update README.md

README.md

@@ -22,11 +22,11 @@ tags:
 - Machine-Learning
 ---
 
-# FinAI-BERT
-FinAI-BERT is a domain-specific BERT-based model fine-tuned for detecting AI-related disclosures in financial texts. 
+# BankAI-BERT
+BankAI-BERT is a domain-specific BERT-based model fine-tuned for detecting AI-related disclosures in banking texts. 
 
 ## Intended Use
-FinAI-BERT is designed to assist researchers, analysts, and regulators in identifying AI narratives in financial disclosures at the sentence level.
+BankAI-BERT is designed to assist researchers, analysts, and regulators in identifying AI narratives in financial disclosures at the sentence level.
 
 ## Performance
 - Accuracy: 99.37%
@@ -35,7 +35,7 @@ FinAI-BERT is designed to assist researchers, analysts, and regulators in identi
 - Brier Score: 0.0000
 
 ## Training Data
-FinAI-BERT was fine-tuned on a manually annotated dataset comprising sentences from U.S. bank annual reports spanning 2015 to 2023. The final training set included a balanced sample of 1,586 sentences—793 labeled as AI-related and 793 as non-AI. The model was initialized using the bert-base-uncased architecture.
+BankAI-BERT was fine-tuned on a manually annotated dataset comprising sentences from U.S. bank annual reports spanning 2015 to 2023. The final training set included a balanced sample of 1,586 sentences—793 labeled as AI-related and 793 as non-AI. The model was initialized using the bert-base-uncased architecture.
 
 ## Training
 | Setting                  | Value |
@@ -70,8 +70,8 @@ Please cite my paper if you use this model:
 ## Usage
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
-tokenizer = AutoTokenizer.from_pretrained("bilalzafar/FinAI-BERT")
-model = AutoModelForSequenceClassification.from_pretrained("bilalzafar/FinAI-BERT")
+tokenizer = AutoTokenizer.from_pretrained("bilalzafar/BankAI-BERT")
+model = AutoModelForSequenceClassification.from_pretrained("bilalzafar/BankAI-BERT")
 
 ## Inference Example
 from transformers import pipeline