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mt5-small-nlu-all-crosswoz – AI Model by ConvLab | AlphaNeural AI

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ConvLab/
mt5-small-nlu-all-crosswoz

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text2text-generation

natural language understanding

conversational system

task-oriented dialog

ConvLab/crosswoz

endpoints_compatible

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mt5-small-nlu-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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 16
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