Create README.md

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- t5-small
+- text2text-generation
+- natural language understanding
+- conversational system
+- task-oriented dialog
+datasets:
+- ConvLab/multiwoz21
+metrics:
+- Dialog acts Accuracy
+- Dialog acts F1
+
+model-index:
+- name: t5-small-nlu-all-multiwoz21
+  results:
+  - task:
+      type: text2text-generation
+      name: natural language understanding
+    dataset:
+      type: ConvLab/multiwoz21
+      name: MultiWOZ 2.1
+      split: test
+      revision: 5f55375edbfe0270c20bcf770751ad982c0e6614
+    metrics:
+      - type: Dialog acts Accuracy
+        value: 69.1
+        name: Accuracy
+      - type: Dialog acts F1
+        value: 83.5
+        name: F1
+
+widget:
+- text: "user: I would like a taxi from Saint John's college to Pizza Hut Fen Ditton."
+- text: "system: What time do you want to leave and what time do you want to arrive by?"
+
+inference:
+  parameters:
+    max_length: 100
+
+---
+
+# t5-small-nlu-all-multiwoz21
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [MultiWOZ 2.1](https://huggingface.co/datasets/ConvLab/multiwoz21) 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: 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 4.20.1
+- Pytorch 1.11.0+cu102
+- Datasets 2.3.2
+- Tokenizers 0.12.1