Update README.md

README.md

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-## TextAttack Model CardThis `albert-base-v2` model was fine-tuned for sequence classification using TextAttack 
-and the glue dataset loaded using the `nlp` library. The model was fine-tuned 
+## TextAttack Model Cardand the glue dataset loaded using the `nlp` library. The model was fine-tuned 
 for 5 epochs with a batch size of 32, a learning 
 rate of 3e-05, and a maximum sequence length of 128. 
 Since this was a classification task, the model was trained with a cross-entropy loss function.