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---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: en
datasets:
- lmqg/qg_squadshifts
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."
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."
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> ."
example_title: "Question Generation Example 3"
model-index:
- name: lmqg/t5-base-squadshifts-nyt
results:
- task:
name: Text2text Generation
type: text2text-generation
dataset:
name: lmqg/qg_squadshifts
type: nyt
args: nyt
metrics:
- name: BLEU4
type: bleu4
value: 0.08526644876436423
- name: ROUGE-L
type: rouge-l
value: 0.2493349672604139
- name: METEOR
type: meteor
value: 0.25210676004231025
- name: BERTScore
type: bertscore
value: 0.9268105589600506
- name: MoverScore
type: moverscore
value: 0.6469994154715311
---
# Language Models Fine-tuning on Question Generation: `lmqg/t5-base-squadshifts-nyt`
This model is fine-tuned version of [lmqg/t5-base-squad](https://huggingface.co/lmqg/t5-base-squad) for question generation task on the
[lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) (dataset_name: nyt).
This model is continuously fine-tuned with [lmqg/t5-base-squad](https://huggingface.co/lmqg/t5-base-squad).
### Overview
- **Language model:** [lmqg/t5-base-squad](https://huggingface.co/lmqg/t5-base-squad)
- **Language:** en
- **Training data:** [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) (nyt)
- **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
- **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
- **Paper:** [TBA](TBA)
### Usage
```python
from transformers import pipeline
model_path = 'lmqg/t5-base-squadshifts-nyt'
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.')
```
## Evaluation Metrics
### Metrics
| Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
|:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
| [lmqg/qg_squadshifts](https://huggingface.co/datasets/lmqg/qg_squadshifts) | nyt | 0.085 | 0.249 | 0.252 | 0.927 | 0.647 | [link](https://huggingface.co/lmqg/t5-base-squadshifts-nyt/raw/main/eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_squadshifts.nyt.json) |
## Training hyperparameters
The following hyperparameters were used during fine-tuning:
- dataset_path: lmqg/qg_squadshifts
- dataset_name: nyt
- input_types: ['paragraph_answer']
- output_types: ['question']
- prefix_types: ['qg']
- model: lmqg/t5-base-squad
- max_length: 512
- max_length_output: 32
- epoch: 5
- batch: 8
- lr: 5e-05
- fp16: False
- random_seed: 1
- gradient_accumulation_steps: 8
- label_smoothing: 0.15
The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/t5-base-squadshifts-nyt/raw/main/trainer_config.json).
## Citation
TBA
|