Update README.md

README.md

@@ -19,7 +19,7 @@ widget:
 
 ## Model description
 
-This model is pre-trained by [UER-py](https://arxiv.org/abs/1909.05658).
+This is the sentence embedding model pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
 
 ## Training data
 
@@ -27,18 +27,17 @@ This model is pre-trained by [UER-py](https://arxiv.org/abs/1909.05658).
 
 ## Training procedure
 
-This model is fine-tuned by [UER-py](https://github.com/dbiir/UER-py/) on [Tencent Cloud](https://cloud.tencent.com/). We fine-tune three epochs with a sequence length of 512 on the basis of the Google's pre-trained Chinese BERT model. At the end of each epoch, the model is saved when the best performance on development set is achieved. 
+The model is fine-tuned by [UER-py](https://github.com/dbiir/UER-py/) on [Tencent Cloud](https://cloud.tencent.com/). We fine-tune five epochs with a sequence length of 128 on the basis of the pre-trained model [chinese_roberta_L-12_H-768](https://huggingface.co/uer/chinese_roberta_L-12_H-768). At the end of each epoch, the model is saved when the best performance on development set is achieved.
 
 ```
-python3 finetune/run_classifier_siamese.py --pretrained_model_path models/google_zh_model.bin \
+python3 finetune/run_classifier_siamese.py --pretrained_model_path models/cluecorpussmall_roberta_base_seq512_model.bin-250000 \
                                            --vocab_path models/google_zh_vocab.txt \
                                            --config_path models/sbert/base_config.json \
                                            --train_path datasets/ChineseTextualInference/train.tsv \
                                            --dev_path datasets/ChineseTextualInference/dev.tsv \
-                                           --epochs_num 3 --batch_size 32
+                                           --learning_rate 5e-5 --epochs_num 5 --batch_size 64
 ```
 
-
 Finally, we convert the pre-trained model into Huggingface's format:
 
 ```
@@ -47,7 +46,6 @@ python3 scripts/convert_sbert_from_uer_to_huggingface.py --input_model_path mode
                                                          --layers_num 12
 ```
 
-
 ### BibTeX entry and citation info
 
 ```