Text Predictor
Character-level RNN (Recurrent Neural Net) LSTM (Long Short-Term Memory) implemented in Python 2.7/TensorFlow in order to predict a text based on a given dataset.
Check out corresponding Medium article:
Text Predictor - Generating Rap Lyrics with Recurrent Neural Networks (LSTMs)
Heavily influenced by: http://karpathy.github.io/2015/05/21/rnn-effectiveness/.
Idea
- Train RNN LSTM on a given dataset (.txt file).
- Predict text based on a trained model.
Datasets
kanye - Kanye West's discography (332 KB)
darwin - the complete works of Charles Darwin (20 MB)
reuters - a collection of Reuters headlines (95 MB)
war_and_peace - Leo Tolstoy's War and Peace novel (3 MB)
wikipedia - excerpt from English Wikipedia (48 MB)
hackernews - a collection of Hackernews headlines (90 KB)
sherlock - a collection of books with Sherlock Holmes (3 MB)
shakespeare - the complete works of William Shakespeare (4 MB)
tagore - short stories by Rabindranath Tagore (2.6 MB)
Feel free to add new datasets. Just create a folder in the ./data
directory and put an input.txt
file there. Output file along with the training plot will be automatically generated there.
Usage
- Clone the repo.
- Go to the project's root folder.
- Install required packages
pip install -r requirements.txt
. python text_predictor.py <dataset>
.
Results
Each dataset were trained with the same hyperparameters.
Hyperparameters
BATCH_SIZE = 32
SEQUENCE_LENGTH = 50
LEARNING_RATE = 0.01
DECAY_RATE = 0.97
HIDDEN_LAYER_SIZE = 256
CELLS_SIZE = 2
Sherlock
Iteration: 0
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Iteration: 500
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Iteration: 1000
some to see me tignaius
rely."
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should not have any take an watchate save now out," said Hodden?"
"Th, a lott remarks. Showed."
"A joan?"
Iteration: 100000
Then mention.""Quite
I gather is stillar in silence was written on the whom I reward an
details grieves of his east back. The week shook this strength.
There was no mystery for y
Hackernews
Iteration: 0
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Iteration: 500
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Iteration: 1000
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Iteration: 100000
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Amit Gupta needs is moving
Shakespeare
Iteration: 0
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Iteration: 500
ticlother them his steaks? whom father-ple plaise't!
HORATIO:
GLOILUS:
Le wime heast,
'Tind soul a bear if thy Gulithes? Preshing;
In beto that mad his says,
Bock Presrike this pray morrombage wenly
Iteration: 1000
HENI:
If which fout in must likest part sors and merr'd?
E sin even and mel full and gooder?
BRUTUS:
Heno Egison to a puenbiloot vieter.
DROMIO OF SYRACUSE:
That is
never standshruced meledder morng
Iteration: 100000
Be feast, tent?
LYSANDER:
And thou love so kiss, to dipate.
All Cornasiers of Atheniansiage are to my sake; but where in end.
APEMANTUS:
Did such a pays. Go, we'll proof.
BERTRAM:
I am reason'dst
War and Peace
Iteration: 0
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Iteration: 500
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Iteration: 1000
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sonison
Iteration: 100000
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tactfully replied that Dolokhov
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Darwin
Iteration: 0
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Iteration: 500
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Iteration: 1000
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Iteration: 100000
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Kanye
Iteration: 0
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Iteration: 1000
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(Had what icherced and I'm nigga"" and some talk to beinn shood late you, fly Me down
Youce, I and fleassy is
Iteration: 10000
as the comphol of step
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Yeah my Benz,.AD and brosi?
Cause you'll take me, breaks to the good I'll never said, ""I met her bitch's pussy is a proll ...
WHO WILL Say everything
We been a minute it's liberatimes?
(Stop that religious and the hegasn of me, steps dead)
I can't contlights you
I bet stop me, I won't you
I cant face and flesed
Tellin' it and sales there
Got a niggas ass a lots over?
So I clay messin 6 wrong baby
Dog, we lose, ""Can't say how I'm heren
Iteration: 231000
right here, history on you
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[Hook]
Good morning!
He wanna kend care helped all wingâĻ the live, man
I'm taking all in my sleep, Im out him and I ain't inspired?
Okay, go you're pastor save being make them
White hit Victure up, it can go down
[Outro: Kanye West]
One time
To make them other you're like Common
A lit it, I'mma bridgeidenace before the most high
Ugh! we get much higher
Tagore
Iteration: 0
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Iteration: 511000
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āĻāĻ˛ā§āĻāĻž āĻāĻ°āĻŋāĻŦā§āĻ¨, 'āĻšā§āĻŽāĻĨāĻžāĻ°āĻž āĻ˛āĻā§āĻˇā§āĻ¯ āĻāĻ°ā§ āĻā§āĻ˛āĨ¤ āĻāĻ¤āĻŋāĻŽāĻ§ā§āĻ¯ā§ āĻ¸āĻŽāĻ¸ā§āĻ¤ āĻ¯āĻ¤ā§āĻ¨ā§ āĻŦāĻžāĻšāĻŋāĻ° āĻšāĻāĻ¤ā§ āĻĒāĻ°āĻŋāĻ¤ā§ āĻšāĻžāĻāĻžāĻ° āĻĻā§āĻĒ
Author
Greg (Grzegorz) Surma