metadata
library_name: keras
tags:
- sentence-similarity
Model description
This repo contains the model and the notebook for fine-tuning BERT model on SNLI Corpus for Semantic Similarity. Semantic Similarity with BERT.
Full credits go to Mohamad Merchant
Reproduced by Vu Minh Chien
Motivation: Semantic Similarity determines how similar two sentences are, in terms of what they mean. The fine-tuned BERT model takes two sentences as inputs and outputs a similarity score for these two sentences.
Training and evaluation data
This example demonstrates the use of SNLI (Stanford Natural Language Inference) Corpus to predict semantic sentence similarity with Transformers.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters | Value |
|---|---|
| name | Adam |
| learning_rate | 9.999999747378752e-06 |
| decay | 0.0 |
| beta_1 | 0.8999999761581421 |
| beta_2 | 0.9990000128746033 |
| epsilon | 1e-07 |
| amsgrad | False |
| training_precision | float32 |
Model Plot
View Model Plot
