Accuracy change with BetterTransformer about optimum HOT 6 OPEN

from transformers import AutoModelForSequenceClassification , AutoTokenizer
from optimum.bettertransformer import BetterTransformer

original_model.half()
transformed_model.half()

tokenizer=AutoTokenizer.from_pretrained("BAAI/bge-reranker-large")

original_model = AutoModelForSequenceClassification.from_pretrained("BAAI/bge-reranker-large").to('cuda:0')
transformed_model = BetterTransformer.transform(original_model, keep_original_model=True).to('cuda:0')

sentences_batch=[['do you like fox cookies', 'fox big brown fox']] 
inputs = tokenizer(sentences_batch,padding=True,truncation=True,return_tensors="pt",max_length=512,).to('cuda:0')

better_transformer_scores = transformed_model(**inputs, return_dict=True).logits.view(-1).float()
print(f"BetterTransfomer output: {better_transformer_scores.detach().cpu().numpy().tolist()}")

vanilla_model_scores = original_model(**inputs, return_dict=True).logits.view(-1).float()
print(f"Vanilla model output :{vanilla_model_scores.detach().cpu().numpy().tolist()}")

BetterTransfomer output: [-7.35546875]
Vanilla model output :[-7.3515625]

sentences_batch=[
    ['do you like fox cookies', 'fox big brown fox']
                 ,['do you like fox cookies', 'fox big big brown fox']
                ,['do you like fox cookies', 'fox small tiny brown fox'],
                 ['n the middl just loading a mookies', 'fox small tiny brown fox  happen in the middl just loading a monthly rollup table']
                ,['do you like fox cookies', 'fox big hello world from the Since most of these loads happen in the middl just loading a monthly rollup table when the regular table load happens. I chose a replace into option, brown fox']
] 

BetterTransfomer output: [-7.35546875, -7.51171875, -8.21875, -1.27734375, -9.4765625]
Vanilla model output :[-7.35546875, -7.515625, -8.2265625, -1.2802734375, -9.4765625]