Create README.md

README.md

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+---
+language:
+- zh
+license: apache-2.0
+tags:
+- mt5-small
+- text2text-generation
+- natural language understanding
+- conversational system
+- task-oriented dialog
+datasets:
+- ConvLab/crosswoz
+metrics:
+- Dialog acts Accuracy
+- Dialog acts F1
+
+model-index:
+- name: mt5-small-nlu-all-crosswoz
+  results:
+  - task:
+      type: text2text-generation
+      name: natural language understanding
+    dataset:
+      type: ConvLab/crosswoz
+      name: CrossWOZ
+      split: test
+      revision: 4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0
+    metrics:
+      - type: Dialog acts Accuracy
+        value: 84.0
+        name: Accuracy
+      - type: Dialog acts F1
+        value: 90.1
+        name: F1
+
+widget:
+- text: "user: 你好，给我推荐一个评分是5分，价格在100-200元的酒店。"
+- text: "system: 抱歉，为您搜索了一些经济型酒店都没有健身房。其他类型的一些酒店行吗？比如北京贵都大酒店、北京京仪大酒店这些也是很好的，就是价格高了一些。"
+
+inference:
+  parameters:
+    max_length: 100
+
+---
+
+# mt5-small-nlu-all-crosswoz
+
+This model is a fine-tuned version of [mt5-small](https://huggingface.co/mt5-small) on [CrossWOZ](https://huggingface.co/datasets/ConvLab/crosswoz) both user and system utterances.
+
+Refer to [ConvLab-3](https://github.com/ConvLab/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