model update

README.md

@@ -70,8 +70,7 @@ model_path = 'lmqg/t5-small-squad-default'
 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_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.2266718077651334 | 0.4953920093132268 | 0.24675728793398077 | 0.9016671782685416 | 0.630633217445346 | [link](https://huggingface.co/lmqg/t5-small-squad-default/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) | 
+| [lmqg/qg_squad](https://huggingface.co/datasets/lmqg/qg_squad) | default | 0.227 | 0.495 | 0.247 | 0.902 | 0.631 | [link](https://huggingface.co/lmqg/t5-small-squad-default/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squad.default.json) |