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23-07-10

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mnist 46% 달성
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jung-geun
2023-07-10 17:05:59 +09:00
parent f18932d6d2
commit 46aa52d81f
8 changed files with 650 additions and 80 deletions
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19
mnist_tf.py
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@@ -60,15 +60,30 @@ model = make_model()
x_train, y_train, x_test, y_test = get_data()
model.compile(
optimizer="sgd", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
)
# model.compile(optimizer="adam", loss="mse", metrics=["accuracy"])
print("Training model...")
model.fit(x_train, y_train, epochs=1000, batch_size=128, verbose=1)
model.fit(x_train, y_train, epochs=100, batch_size=128, verbose=1)
print("Evaluating model...")
model.evaluate(x_test, y_test, verbose=1)
weights = model.get_weights()
for w in weights:
print(w.shape)
print(w)
print(w.min(), w.max())
model.save_weights("weights.h5")
# %%
for w in weights:
print(w.shape)
print(w)
print(w.min(), w.max())
# %%