sts_config['sts_loss_weight'], sts_config['sts_batch_size'])
original_sentence_precision = ClassWisePrecision(
cls_config['original_sentence_label'], name='precision_original_sentence')
changed_sentence_precision = ClassWisePrecision(
cls_config['changed_sentence_label'], name='precision_changed_sentence')
original_sentence_recall = ClassWiseRecall(
cls_config['original_sentence_label'], name='recall_original_sentence')
changed_sentence_recall = ClassWiseRecall(cls_config['changed_sentence_label'],
name='recall_changed_sentence')
model.compile(optimizer=tf.keras.optimizers.Adam(
learning_rate=train_config['learning_rate']),
loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
metrics=[
tf.keras.metrics.BinaryAccuracy(threshold=0.0),
original_sentence_precision, changed_sentence_precision,
original_sentence_recall, changed_sentence_recall
])
INIT_EPOCH = train_config['starting_epoch']
NUM_EPOCHS = train_config['num_epochs']
model.fit(train_ds,
validation_data=val_ds,
epochs=INIT_EPOCH + NUM_EPOCHS,
initial_epoch=INIT_EPOCH,
callbacks=[sts_eval_callback, cp_callback])
""" Write model config into json file """
config_json_path = os.path.join(current_model_folder, "model_config.json")
with open(config_json_path, 'w') as json_file:
