INNER CODE UNIT · Python
duration
yuhaozhang/tacred-relation · train.py:120
duration = time.time() - start_time
print(format_str.format(datetime.now(), global_step, max_steps, epoch,\
opt['num_epoch'], loss, duration, current_lr))
# eval on dev
print("Evaluating on dev set...")
predictions = []
dev_loss = 0
for i, batch in enumerate(dev_batch):
preds, _, loss = model.predict(batch)
predictions += preds
dev_loss += loss
predictions = [id2label[p] for p in predictions]
dev_p, dev_r, dev_f1 = scorer.score(dev_batch.gold(), predictions)
train_loss = train_loss / train_batch.num_examples * opt['batch_size'] # avg loss per batch
dev_loss = dev_loss / dev_batch.num_examples * opt['batch_size']
print("epoch {}: train_loss = {:.6f}, dev_loss = {:.6f}, dev_f1 = {:.4f}".format(epoch,\