ke_contrastive_learning/simcse/losses/0: 11.9251 - val_BertMultiTaskTop/weibo_fake_cls/losses/0: 0.9174 - val_BertMultiTaskTop/weibo_fake_multi_cls/losses/0: 0.4063 - val_BertMultiTaskTop/weibo_fake_ner/losses/0: 1.4417 - val_BertMultiTaskTop/weibo_fake_regression/losses/0: 1.0292 - val_BertMultiTaskTop/weibo_fake_vector_fit/losses/0: 0.3355 - val_BertMultiTaskTop/weibo_masklm/losses/0: 9.9006 - val_BertMultiTaskTop/weibo_premask_mlm/losses/0: 9.7633
</pre>
</div>
</div>

</div>
</div>

</div>
    {% endraw