model update

README.md

@@ -7,21 +7,21 @@ metrics:
 - rouge-l
 - bertscore
 - moverscore
-language: en
+language: de
 datasets:
 - lmqg/qg_dequad
 pipeline_tag: text2text-generation
 tags:
 - question generation
 widget:
-- text: "<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
+- text: "Empfangs- und Sendeantenne sollen in ihrer Polarisation übereinstimmen, andernfalls <hl> wird die Signalübertragung stark gedämpft. <hl>"
   example_title: "Question Generation Example 1" 
-- text: "Beyonce further expanded her acting career, starring as blues singer <hl> Etta James <hl> in the 2008 musical biopic, Cadillac Records."
+- text: "das erste weltweit errichtete Hermann Brehmer <hl> 1855 <hl> im niederschlesischen ''Görbersdorf'' (heute Sokołowsko, Polen)."
   example_title: "Question Generation Example 2" 
-- text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic,  <hl> Cadillac Records <hl> ."
+- text: "Er muss Zyperngrieche sein und wird direkt für <hl> fünf Jahre <hl> gewählt (Art. 43 Abs. 1 der Verfassung) und verfügt über weitreichende Exekutivkompetenzen."
   example_title: "Question Generation Example 3" 
 model-index:
-- name: lmqg/mt5-small-dequad
+- name: lmqg/mt5-small-dequad-qg
   results:
   - task:
       name: Text2text Generation
@@ -66,13 +66,13 @@ model-index:
       value: 64.37
 ---
 
-# Model Card of `lmqg/mt5-small-dequad`
+# Model Card of `lmqg/mt5-small-dequad-qg`
 This model is fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) for question generation task on the [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
 
 
 ### Overview
 - **Language model:** [google/mt5-small](https://huggingface.co/google/mt5-small)   
-- **Language:** en  
+- **Language:** de  
 - **Training data:** [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) (default)
 - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
 - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
@@ -84,10 +84,10 @@ This model is fine-tuned version of [google/mt5-small](https://huggingface.co/go
 from lmqg import TransformersQG
 
 # initialize model
-model = TransformersQG(language="en", model="lmqg/mt5-small-dequad")
+model = TransformersQG(language="de", model="lmqg/mt5-small-dequad-qg")
 
 # model prediction
-questions = model.generate_q(list_context="William Turner was an English painter who specialised in watercolour landscapes", list_answer="William Turner")
+questions = model.generate_q(list_context="das erste weltweit errichtete Hermann Brehmer 1855 im niederschlesischen ''Görbersdorf'' (heute Sokołowsko, Polen).", list_answer="1855")
 
 ```
 
@@ -95,15 +95,15 @@ questions = model.generate_q(list_context="William Turner was an English painter
 ```python
 from transformers import pipeline
 
-pipe = pipeline("text2text-generation", "lmqg/mt5-small-dequad")
-output = pipe("<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")
+pipe = pipeline("text2text-generation", "lmqg/mt5-small-dequad-qg")
+output = pipe("Empfangs- und Sendeantenne sollen in ihrer Polarisation übereinstimmen, andernfalls <hl> wird die Signalübertragung stark gedämpft. <hl>")
 
 ```
 
 ## Evaluation
 
 
-- ***Metric (Question Generation)***: [raw metric file](https://huggingface.co/lmqg/mt5-small-dequad/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_dequad.default.json) 
+- ***Metric (Question Generation)***: [raw metric file](https://huggingface.co/lmqg/mt5-small-dequad-qg/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_dequad.default.json) 
 
 |            |   Score | Type    | Dataset                                                          |
 |:-----------|--------:|:--------|:-----------------------------------------------------------------|
@@ -117,7 +117,7 @@ output = pipe("<hl> Beyonce <hl> further expanded her acting career, starring as
 | ROUGE_L    |   10.08 | default | [lmqg/qg_dequad](https://huggingface.co/datasets/lmqg/qg_dequad) |
 
 
-- ***Metric (Question & Answer Generation)***: QAG metrics are computed with *the gold answer* and generated question on it for this model, as the model cannot provide an answer. [raw metric file](https://huggingface.co/lmqg/mt5-small-dequad/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_dequad.default.json)
+- ***Metric (Question & Answer Generation)***: QAG metrics are computed with *the gold answer* and generated question on it for this model, as the model cannot provide an answer. [raw metric file](https://huggingface.co/lmqg/mt5-small-dequad-qg/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qg_dequad.default.json)
 
 |                                 |   Score | Type    | Dataset                                                          |
 |:--------------------------------|--------:|:--------|:-----------------------------------------------------------------|
@@ -149,7 +149,7 @@ The following hyperparameters were used during fine-tuning:
  - gradient_accumulation_steps: 4
  - label_smoothing: 0.15
 
-The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-small-dequad/raw/main/trainer_config.json).
+The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/mt5-small-dequad-qg/raw/main/trainer_config.json).
 
 ## Citation
 ```