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# Sentiment Analysis with GUI
A Deep Learning Model which used for Sentiment analysis. The Accuracy it reach upto 85%. It train on 25000 text data.
# Neural Network Info
The bert layer is integrated in the neural network at the second layer after input layer. The 3 GRU layer is for feature extraction
then a Conv1D Layer is use after that making the output flatten and passing through a bunch of dense layer.
## Info
1) "Bert_uncased_model_Tiwtter.h5" has reached to the accuracy upto 85% just on 30 epochs. Loss it got is 0.51. This model is purly train in Twitter dataset.

2) "Bert_uncased_model_Reddit.h5" has reached to the accuracy upto 84% just on 35 epochs. Loss it got is 0.81. This model is not purly train in Twitter dataset but a bit of reddit's dataset is also used.

Loss :- Sparse_categorical_crossentropy
Activatiion on last layer :- softmax
Note: Max input length is 768 words.
## Screenshots





## Libray Used
##### > opencv
##### > tensorflow
##### > numpy
##### > pickle
##### > bert
##### > tensorflow_hub
##### > tensorflow_text
## Authors
- [@Somnath Dash](https://www.github.com/somnathdashs)
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