t5-small-nlu-sgd
This model is a fine-tuned version of t5-small on Schema-Guided Dialog.
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: 128
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- 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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Dataset used to train ConvLab/t5-small-nlu-sgd
Evaluation results
- Accuracy on SGDtest set self-reported45.000
- F1 on SGDtest set self-reported58.600