slendi/uwu_classifier
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Improve interactive.

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Signed-off-by: Slendi <slendi@socopon.com>
This commit is contained in:
Slendi 2023-11-05 01:49:19 +02:00
parent b57e8d00f6
commit 00d3d9218d
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GPG Key ID: FEE30F374BAC2C78
2 changed files with 8 additions and 2 deletions
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8
interactive.py
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@ -13,4 +13,10 @@ with tf.keras.utils.CustomObjectScope({'text_standardizer': text_standardizer}):
model.summary() model.summary()
while True: while True:
print(model.predict([input('> ')])) inp = [i.strip() for i in input('> ').split('.')]
while "" in inp:
inp.remove("")
output = model.predict(inp)
score = sum(output) / len(output)
print(["UwU" if i > 0.5 else "Normal" for i in output])
print("Final judgement:", "UwU" if score > 0.5 else "Normal")

2
train.py
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@ -101,7 +101,7 @@ model.compile(loss=losses.BinaryCrossentropy(from_logits=True),
optimizer='adam', optimizer='adam',
metrics=tf.metrics.BinaryAccuracy(threshold=0.0)) metrics=tf.metrics.BinaryAccuracy(threshold=0.0))
epochs = 10 epochs = 12
history = model.fit( history = model.fit(
train_ds, train_ds,
validation_data=val_ds, validation_data=val_ds,