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---
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](https://keras.io/examples/nlp/semantic_similarity_with_bert/).
Full credits go to [Mohamad Merchant](https://twitter.com/mohmadmerchant1)
Reproduced by [Vu Minh Chien](https://www.linkedin.com/in/vumichien/)
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
<details>
<summary>View Model Plot</summary>
</details> |