t5-small-nlg-multiwoz21_sgd_tm1_tm2_tm3
This model is a fine-tuned version of t5-small on MultiWOZ 2.1, Schema-Guided Dialog, Taskmaster-1, Taskmaster-2, and Taskmaster-3.
Refer to ConvLab-3 for model description and usage.
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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Datasets used to train ConvLab/t5-small-nlg-multiwoz21_sgd_tm1_tm2_tm3
Evaluation results
- SER on MultiWOZ 2.1test set self-reported3.200
- BLEU on MultiWOZ 2.1test set self-reported35.600
- SER on SGDtest set self-reported8.300
- BLEU on SGDtest set self-reported29.900
- SER on TM1+TM2+TM3test set self-reported2.000
- BLEU on TM1+TM2+TM3test set self-reported51.300