model update

README.md

@@ -70,8 +70,7 @@ model_path = 'lmqg/t5-small-subjqa-vanilla-restaurants'
 pipe = pipeline("text2text-generation", model_path)
 
 # Question Generation
-input_text = 'generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.'
-question = pipe(input_text)
+question = pipe('generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
 ```
 
 ## Evaluation Metrics
@@ -81,7 +80,7 @@ question = pipe(input_text)
 
 | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
 |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
-| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | restaurants | 1.5194344626336288e-14 | 0.007328137742159685 | 0.00974946931702154 | 0.12266698917921852 | 0.4945447139781372 | [link](https://huggingface.co/lmqg/t5-small-subjqa-vanilla-restaurants/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.restaurants.json) | 
+| [lmqg/qg_subjqa](https://huggingface.co/datasets/lmqg/qg_subjqa) | restaurants | 0.0 | 0.007 | 0.01 | 0.123 | 0.495 | [link](https://huggingface.co/lmqg/t5-small-subjqa-vanilla-restaurants/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_subjqa.restaurants.json) |