mt5-small-dst-crosswoz
This model is a fine-tuned version of mt5-small on CrossWOZ.
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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Dataset used to train ConvLab/mt5-small-dst-crosswoz
Evaluation results
- JGA on CrossWOZtest set self-reported62.500
- Slot F1 on CrossWOZtest set self-reported90.400