model update

README.md

@@ -14,11 +14,11 @@ pipeline_tag: text2text-generation
 tags:
 - question generation
 widget:
-- text: "generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
+- text: "<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
   example_title: "Question Generation Example 1" 
-- text: "generate question: Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
+- text: "Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
   example_title: "Question Generation Example 2" 
-- text: "generate question: Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic,  <hl> Cadillac Records <hl> ."
+- text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic,  <hl> Cadillac Records <hl> ."
   example_title: "Question Generation Example 3" 
 model-index:
 - name: lmqg/mt5-base-dequad
@@ -70,7 +70,7 @@ model_path = 'lmqg/mt5-base-dequad'
 pipe = pipeline("text2text-generation", model_path)
 
 # Question Generation
-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.')
+question = pipe('<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
 ```
 
 ## Evaluation Metrics
@@ -80,7 +80,7 @@ question = pipe('generate question: <hl> Beyonce <hl> further expanded her actin
 
 | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
 |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
-| [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) | default | 0.008725076003212685 | 0.11103265327794129 | 0.1365307725077819 | 0.803881755792351 | 0.5572775810948901 | [link](https://huggingface.co/lmqg/mt5-base-dequad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_dequad.default.json) | 
+| [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) | default | 0.009 | 0.111 | 0.137 | 0.804 | 0.557 | [link](https://huggingface.co/lmqg/mt5-base-dequad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_dequad.default.json) |