t5-large-coqr-canard
This model is a fine-tuned version of t5-large on the CANARD dataset. It achieves the following results on the test set:
- Loss: 0.3064
- Bleu: 77.1979
- Generation Length: 9.576
Model description
CANARD dataset rewrites the original questions in conversations to make them context-independent (understandable w/o context). On the contrary, this model is trained to rewrite context-independent questions to conversational questions, aiming to create fluent dialog with anaphora and ellipsis.
Input:
Rewrite the question according to the given context to make the dialog fluent using anaphora and ellipsis.
question: How did people respond to Superstar Billy Graham's return?
context: Superstar Billy Graham
Return to WWWF (1977-1981)
Why did he return to the WWWF?
an agreement with promoter Vincent J. McMahon (Senior
What was his agreement with McMahon?
I don't know.
Target:
How did people respond to his return?
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 512
- total_eval_batch_size: 512
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 62 | 0.2987 | 77.2361 | 9.4534 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1
