Update README.md

README.md

@@ -1,29 +1,53 @@
 ---
+language:
+- en
+license: apache-2.0
 tags:
-- generated_from_trainer
-model-index:
-- name: context_100
-  results: []
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+- t5-small
+- text2text-generation
+- dialog state tracking
+- conversational system
+- task-oriented dialog
+datasets:
+- ConvLab/sgd
+metrics:
+- Joint Goal Accuracy
+- Slot F1
 
-# context_100
-
-This model is a fine-tuned version of [output/dst/sgd/user/context_100](https://huggingface.co/output/dst/sgd/user/context_100) on an unknown dataset.
+model-index:
+- name: t5-small-dst-sgd
+  results:
+  - task:
+      type: text2text-generation
+      name: dialog state tracking
+    dataset:
+      type: ConvLab/sgd
+      name: SGD
+      split: test
+      revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f
+    metrics:
+      - type: Joint Goal Accuracy
+        value: 52.6
+        name: JGA
+      - type: Slot F1
+        value: 91.9
+        name: Slot F1
 
-## Model description
+widget:
+- text: "user: Hi, could you get me a restaurant booking on the 8th please?\nsystem: Any preference on the restaurant, location and time?\nuser: Could you get me a reservation at P.f. Chang's in Corte Madera at afternoon 12?"
+- text: "user: I need to book a dinner reservation for a date. Help me reserve a table at a restaurant.\nsystem: What time and location do you have in mind?\nuser: Something around 8 in the night should be fine. Oh, and look in the San Jose area."
 
-More information needed
+inference:
+  parameters:
+    max_length: 100
 
-## Intended uses & limitations
+---
 
-More information needed
+# t5-small-dst-sgd
 
-## Training and evaluation data
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [Schema-Guided Dialog](https://huggingface.co/datasets/ConvLab/sgd).
 
-More information needed
+Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage.
 
 ## Training procedure
 
@@ -31,11 +55,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.001
-- train_batch_size: 64
+- train_batch_size: 128
 - eval_batch_size: 64
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 128
+- total_train_batch_size: 256
 - optimizer: Adafactor
 - lr_scheduler_type: linear
 - num_epochs: 10.0