纪元2: 23%| 3/13 01:44<05:47,34.72s/it,loss=2.72,v_num=7,██▎ //training_epoch_end:输出= {'loss':张量(1.2504)},{'loss':张量(1.4905)},{'loss':张量(1.4158)} 纪元2: 31%| 01:49<04:07 | 4/13秒,27.48秒/秒,loss=2.72,v_num=7,███ 正在验证: 0it 00:00,?it/s 纪...
对于问答任务,作者把问题和段落的序列作为A和B输入到模型中,使用开始符S和结束符E作为下游任务的输入。对段落中每个单词Ti都乘以S,然后套一个softmax,就是该单词为答案span的start的概率,end同理(这种用start和end来标记段落中答案的方法非常常见)。公式如下所示: image.png 作者经过5个epoch就能完成精调。 image...
此外,我们还展示了我们的模型在更广泛的任务范围内的有效性,包括自然语言推理、释义检测和故事完成。 辅助训练目标:添加辅助的无监督训练目标是半监督学习的另一种形式。Collobert和Weston (2008)的工作使用了各种辅助NLP任务,如词性标注、分块、命名实体识别和语言建模,以改进语义角色标注。最近,Rei(2017)在他们的目标...
trainer = Trainer(reload_dataloaders_every_n_epochs=0 # 每5个epoch 重新加载dataload)
现在让我们使用 3 个 epoch 。所以我们将循环遍历 epoch ,每个 epoch 都会遍历我们的数据。就像是: for epoch in range(3): # 3 full passes over the data for data in trainset: # `data` is a batch of data X, y = data # X is the batch of features, y is the batch of targets. net....
当迭代的次数self.counter大于self.len的时候, 即经过了一个epoch,重新对负样本的索引进行随机抽取,已经被抽取到的负样本的概率减少,没有被抽取到的负样本的概率增加 上述的好处,1. 每一个epoch过程中,正样本和负样本的个数是一样的 2.每一个负样本被抽取的概率是接近的。
importnumpyasnpimporttensorflow.kerasaskerasimportresourceclassMemoryCallback(keras.callbacks.Callback):defon_epoch_end(self, epoch, log={}):print(resource.getrusage(resource.RUSAGE_SELF).ru_maxrss)defbuild_model(shape): f_input = keras.layers.Input(shape=(shape[1],))# (100,)d1 = keras.laye...
in ModelCheckpoint the variableself.bestis the loss value of the previously saved best model. This quantity is compared to the currentval_loss(varibalecurrentin on_epoch_end, line 424) at the end of the specified epoch, and based on that a model with lower loss is saved (or higher accur...
options = TrainingOptionsSGDM with properties: Momentum: 0.9000 InitialLearnRate: 0.0100 MaxEpochs: 20 LearnRateSchedule: 'piecewise' LearnRateDropFactor: 0.2000 LearnRateDropPeriod: 5 MiniBatchSize: 64 Shuffle: 'once' CheckpointFrequency: 1 CheckpointFrequencyUnit: 'epoch' SequenceLength: 'longest' Pr...
Download dataset from http://trillionpairs.deepglint.com/data (after signup). msra is a cleaned subset of MS1M from glint while celebrity is the asian dataset. Generate lst file by calling src/data/glint2lst.py. For example: python glint...