Source Code for "Frame Semantic Role Labeling Using Arbitrary-Order Conditional Random Fields" at AAAI-2024.
Our code is based on AGED, thanks for their great work!
The preprocessed FrameNet 1.5 and 1.7 data are the same as AGED.
We show the hyper-parameter settings in the following table.
| Hyper-parameters | Value |
|---|---|
| Pretrained Language Model | bert-base-uncased |
| BERT embedding dimension | 768 |
| batch size | 32 |
| optimizer | BertAdam |
| scheduler | linear warmup |
| warmup ratio (train only) | 0.05 |
| warmup ratio (pretrain) | 0.01 |
| warmup ratio (fine-tune) | 0.05 |
| learning rate (train only) | 5e-5 |
| learning rate (pretrain) | 5e-5 |
| learning rate (fine-tune) | 2.5e-5 |
| gradient clipping | 5.0 |
| MLP layers | 1 |
| MLP activation function | ReLU |
| MLP dimension | 768 |
| rank dimension | 512 |
| mean-field inference iterations | 3 |
| epoch num (train only) | 20 |
| epoch num (pretrain) | 5 |
| epoch num (finetune) | 10 |
bash first.sh
bash first_pretrain.sh
bash arbitrary.sh
bash arbitrary_pretrain.sh