Update README.md

README.md

@@ -17,31 +17,88 @@ widget:
 
 ## Model description
 
-This model is a **Candidate Set Generator** in **"CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language Model"** at **Findings of EMNLP 2022**.
+This model is a Candidate Set Generator in **"CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language Model", Findings of EMNLP 2022**.
 
-Its input are stem and answer, and output is candidate set. It is fine-tuned by [CLOTH](https://github.com/AndyChiangSH/CDGP/blob/main/datasets/CLOTH.zip) dataset based on [bert-base-uncased](https://huggingface.co/bert-base-uncased) model.
+Its input are stem and answer, and output is candidate set of distractors. It is fine-tuned by [**CLOTH**](https://www.cs.cmu.edu/~glai1/data/cloth/) dataset based on [**bert-base-uncased**](https://huggingface.co/bert-base-uncased) model.
 
-For more details, you can see our paper or [GitHub](https://).
+For more details, you can see our paper or [GitHub](https://github.com/AndyChiangSH/CDGP).
 
 ## How to use?
 
+1. Download model by hugging face transformers.
+```python
+from transformers import BartTokenizer, BartForConditionalGeneration
 
+tokenizer = BartTokenizer.from_pretrained("AndyChiang/cdgp-csg-bert-cloth")
+csg_model = BartForConditionalGeneration.from_pretrained("AndyChiang/cdgp-csg-bert-cloth")
+```
+
+2. Create a unmasker.
+```python
+unmasker = pipeline('fill-mask', tokenizer=tokenizer, model=csg_model, top_k=10)
+```
+
+3. Use the unmasker to generate the candidate set of distractors.
+```python
+sent = "I feel [MASK] now. [SEP] happy"
+cs = unmasker(sent)
+print(cs)
+```
 
 ## Dataset
 
-More information needed
+This model is fine-tuned by [**CLOTH**](https://www.cs.cmu.edu/~glai1/data/cloth/) dataset, which is a collection of nearly 100,000 cloze questions from middle school and high school English exams. The detail of CLOTH dataset is shown below.
+
+| Number of questions | Train | Valid | Test  |
+| ------------------- | ----- | ----- | ----- |
+| Middle school       | 22056 | 3273  | 3198  |
+| High school         | 54794 | 7794  | 8318  |
+| Total               | 76850 | 11067 | 11516 |
+
+You can also use the [dataset](https://github.com/AndyChiangSH/CDGP/blob/main/datasets/CLOTH.zip) we have already cleaned.
 
 ## Training
 
+We use a special way to fine-tune model, which is called **"Answer-Relating Fine-Tune"**. More detail is in our paper.
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: None
-- training_precision: float32
+
+- Pre-train language model: [bert-base-uncased](https://huggingface.co/bert-base-uncased)
+- Optimizer: adam
+- Learning rate: 0.0001
+- Max length of input: 64
+- Batch size: 64
+- Epoch: 1
+- Device: NVIDIA® Tesla T4 in Google Colab 
 
 ## Testing
 
-## Model list
+The evaluations of CDPG with  are shown in the table below.
+
+The evaluations of this model as a Candidate Set Generator in CDGP is as follows:
+
+| P@1   | F1@3  | F1@10 | MRR   | NDCG@10 |
+| ----- | ----- | ----- | ----- | ------- |
+| 18.50 | 13.80 | 15.37 | 29.96 | 37.82   |
+
+## Other models
+
+### Candidate Set Generator
+
+| Models      | CLOTH                                                                               | DGen                                                                             |
+| ----------- | ----------------------------------------------------------------------------------- | -------------------------------------------------------------------------------- |
+| **BERT**    | [*cdgp-csg-bert-cloth*](https://huggingface.co/AndyChiang/cdgp-csg-bert-cloth)        | [cdgp-csg-bert-dgen](https://huggingface.co/AndyChiang/cdgp-csg-bert-dgen)       |
+| **SciBERT** | [cdgp-csg-scibert-cloth](https://huggingface.co/AndyChiang/cdgp-csg-scibert-cloth)  | [cdgp-csg-scibert-dgen](https://huggingface.co/AndyChiang/cdgp-csg-scibert-dgen) |
+| **RoBERTa** | [Acdgp-csg-roberta-cloth](https://huggingface.co/AndyChiang/cdgp-csg-roberta-cloth) | [cdgp-csg-roberta-dgen](https://huggingface.co/AndyChiang/cdgp-csg-roberta-dgen) |
+| **BART**    | [cdgp-csg-bart-cloth](https://huggingface.co/AndyChiang/cdgp-csg-bart-cloth)        | [cdgp-csg-bart-dgen](https://huggingface.co/AndyChiang/cdgp-csg-bart-dgen)       |
+
+### Distractor Selector
+
+**fastText**: [cdgp-ds-fasttext](https://huggingface.co/AndyChiang/cdgp-ds-fasttext)
+
+
+## Citation
 
-## Citation
+None