我有一個在 tensorflow 上運行的 CNN 模型，并且想將準確率、損失、f1、精度和召回值保存為，我還有圖和混淆矩陣（你可以將這些圖保存到 csv 嗎？）我想保存。如何將每個模型運行時的這些資料保存到 csv 或文本檔案中？
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嘗試使用tf.keras.callbacks.CSVLogger：
import tensorflow as tf
import pandas as pd
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(1, input_dim=40))
model.add(tf.keras.layers.Dense(1, 'sigmoid'))
adam_opt = tf.keras.optimizers.Adam(0.1)
model.compile(loss='bce', optimizer=adam_opt, metrics=[tf.keras.metrics.BinaryAccuracy(name="binary_accuracy", dtype=None),
tf.keras.metrics.Recall()])
train_x = tf.random.normal((50, 40))
train_y = tf.random.uniform((50, 1), maxval=2, dtype=tf.int32)
val_x = tf.random.normal((50, 40))
val_y = tf.random.uniform((50, 1), maxval=2, dtype=tf.int32)
csv_logger = tf.keras.callbacks.CSVLogger('metrics.csv')
history = model.fit(train_x, train_y, epochs=5, validation_data=(val_x, val_y), callbacks=[csv_logger])
df = pd.read_csv('/content/metrics.csv')
print(df.to_markdown())
Epoch 1/5
2/2 [==============================] - 2s 563ms/step - loss: 0.7918 - binary_accuracy: 0.4400 - recall: 0.4583 - val_loss: 0.7283 - val_binary_accuracy: 0.4200 - val_recall: 0.4815
Epoch 2/5
2/2 [==============================] - 0s 62ms/step - loss: 0.6793 - binary_accuracy: 0.5400 - recall: 0.5417 - val_loss: 0.7093 - val_binary_accuracy: 0.4200 - val_recall: 0.2593
Epoch 3/5
2/2 [==============================] - 0s 92ms/step - loss: 0.6647 - binary_accuracy: 0.6200 - recall: 0.3750 - val_loss: 0.7138 - val_binary_accuracy: 0.4400 - val_recall: 0.2222
Epoch 4/5
2/2 [==============================] - 0s 68ms/step - loss: 0.6369 - binary_accuracy: 0.6200 - recall: 0.3750 - val_loss: 0.7340 - val_binary_accuracy: 0.4400 - val_recall: 0.3704
Epoch 5/5
2/2 [==============================] - 0s 69ms/step - loss: 0.5869 - binary_accuracy: 0.6800 - recall: 0.5417 - val_loss: 0.7975 - val_binary_accuracy: 0.4800 - val_recall: 0.4444
| 時代 | binary_accuracy | 損失 | 記起 | val_binary_accuracy | val_loss | val_recall | |
|---|---|---|---|---|---|---|---|
| 0 | 0 | 0.44 | 0.791773 | 0.458333 | 0.42 | 0.728296 | 0.481481 |
| 1 | 1 | 0.54 | 0.67928 | 0.541667 | 0.42 | 0.709347 | 0.259259 |
| 2 | 2 | 0.62 | 0.664661 | 0.375 | 0.44 | 0.713829 | 0.222222 |
| 3 | 3 | 0.62 | 0.636919 | 0.375 | 0.44 | 0.734033 | 0.37037 |
| 4 | 4 | 0.68 | 0.586907 | 0.541667 | 0.48 | 0.797542 | 0.444444 |
訓練后，您可以輕松地使用 csv 檔案進行繪圖。
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標籤：Python 张量流 喀拉斯 卷积神经网络 张量流2.0