mt5-small-nlg-all-crosswoz
This model is a fine-tuned version of mt5-small on CrossWOZ both user and system utterances.
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10.0
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
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Dataset used to train ConvLab/mt5-small-nlg-all-crosswoz
Evaluation results
- SER on CrossWOZtest set self-reported6.900
- BLEU on CrossWOZtest set self-reported21.000