Comments (6)
Yes you are right. We tested multiple loss functions during experiments. The released code used l1 norm between the sentence embedding and triple embedding indeed. It is not hard to modify it to the NCE-like loss form. We could supplement it in case it is required.
from deepex.
Thanks for your apply. I would appreciate it if you could add NCE loss and the relevant training process.
from deepex.
Thanks for your apply. I would appreciate it if you could add NCE loss and the relevant training process.
Hi! After checking it again, it is worth noting that the code in the Ranking function is used for inference only. It actually does not matter too much what exact function is used for computing inference score as long as the order is maintained.
Our training code uses the loss described in Equation (1). We are still organizing the training scripts and they will be released soon.
from deepex.
Thanks for your apply. I look forward to your release of the training scripts.
from deepex.
The training scripts will be released soon. I'll close this issue and we will pin you once the scripts are released.
from deepex.
Thank you for great work. Where can I find the training scripts?
from deepex.
Related Issues (16)
- Regarding the Task-agnostic Corpus HOT 1
- Evaluation on BenchIE HOT 2
- git clone时出现问题
- The file of P0_result.json is empty HOT 1
- Reproducing results shown in paper HOT 3
- Running inference on sentences HOT 4
- Would script about model "Magolor/deepex-ranking-model" be released?
- Unable to run bash tasks/OIE_2016.sh HOT 1
- Poor triple extractor performance (OpenIE) HOT 4
- Would script about model "Magolor/deepex-ranking-model" be released? HOT 4
- Help running inference HOT 2
- About the reproduce results of deepex HOT 3
- 关于OIE数据集中指标比较的疑惑 HOT 2
- 测试 Born in Glasgow, Fisher is a graduate of the London Opera Centre 生成三元组结果 HOT 6
- Details of output from OIE_2016.sh HOT 2
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from deepex.