fudnet
This model is a fine-tuned version of setu4993/LaBSE on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1370
- Accuracy: 0.9537
Model description
FUDNet is for Follow-Up Detector Net. This model takes two consequtive questions of a multidoc2dial question answering conversation and determines whether those two questions are from the same documents or not.
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1946 | 1.0 | 732 | 0.1493 | 0.9453 |
| 0.0945 | 2.0 | 1464 | 0.1370 | 0.9537 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.12.1+cu113
- Datasets 2.0.0
- Tokenizers 0.12.1