Create README.md

README.md

@@ -0,0 +1,72 @@
+---
+language:
+- zh
+license: apache-2.0
+tags:
+- mt5-small
+- text2text-generation
+- natural language generation
+- conversational system
+- task-oriented dialog
+datasets:
+- ConvLab/crosswoz
+metrics:
+- Slot Error Rate
+- sacrebleu
+
+model-index:
+- name: mt5-small-nlg-all-crosswoz
+  results:
+  - task:
+      type: text2text-generation
+      name: natural language generation
+    dataset:
+      type: ConvLab/crosswoz
+      name: CrossWOZ
+      split: test
+      revision: 4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0
+    metrics:
+      - type: Slot Error Rate
+        value: 6.9
+        name: SER
+      - type: sacrebleu
+        value: 21.0
+        name: BLEU
+
+widget:
+- text: "[Inform][酒店]([价格][100-200元],[评分][5分]);[greet][General]([][]);[Request][酒店]([名称][])\n\nuser: "
+- text: "[Recommend][酒店]([名称][北京京仪大酒店],[名称][北京贵都大酒店]);[Inform][酒店]([酒店设施-健身房-否][]);[NoOffer][酒店]([][])\n\nsystem: "
+
+inference:
+  parameters:
+    max_length: 100
+
+---
+
+# mt5-small-nlg-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: 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