Comments (4)
Hi! I'm not pretty sure if I understand your question correctly, but our approach doesn't train the entity and relation models together. We need to train the entity model first to provide entity information for the relation model.
If you actually want a code to train two models sequentially, it should be straightforward to include training commands for both models in a bash script.
Let me know if you have further questions!
from pure.
Hi! I'm not pretty sure if I understand your question correctly, but our approach doesn't train the entity and relation models together. We need to train the entity model first to provide entity information for the relation model.
If you actually want a code to train two models sequentially, it should be straightforward to include training commands for both models in a bash script.
Let me know if you have further questions!
In Section 5.2, how to implement sharing of two representation encoders? thanks!
from pure.
Hi! To share the encoders during training, you can create training set combining entity training instances and relation training instances. At each iteration, random select a training batch from either entity instances or relation instances, compute the loss and update the shared model.
I currently don't have a plan to release this code, but it should be straightforward to implement this based on the current code. Let me know if you need any further help!
from pure.
Thank you!
from pure.
Related Issues (20)
- Multiple issues HOT 2
- different F1 with the same seed HOT 2
- tensorflow版本 HOT 1
- About the relation in datasets HOT 1
- [Paper] What are "gold" entity and relationship types? HOT 2
- Provide full environment
- Input Data Format HOT 5
- How to load models into Python HOT 2
- some code problems reguarding run_relation_approx(get_features_from_file) HOT 2
- where is the code of Efficient Batch Computations
- Approximation Model Training & Inference HOT 1
- entity is S or O ?
- Further question of f1 and e2e_f1
- 版本库问题 HOT 1
- 版本库问题
- ACE dataset
- Training a model on a dataset that is not ace04, ace05, or scierc HOT 1
- training model for WLP -- stuck in suboptimal solution
- Input data format question for custom dataset !
- cuda out of memory
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