add log info and clean up text

src/about.py

@@ -75,13 +75,16 @@ In our Adversarial Calibration QA task, we evaluate the QA model's reliability o
 
 ## FAQ
 What if my system type is not specified here or not supported yet?
-- Please have a private post to instructors so we could check how we could adapt the leaderboard for your purpose. Thanks!
+- Please send us an email so we could check how we adapt the leaderboard for your purpose. Thanks!
 
 I don't understand where I could start to build a QA system for submission.
 - Please check our submission tutorials. From there, you could fine-tune or do anything above the base models.
 
 I want to use API-based QA systems for submission, like GPT4. What should I do?
 - We don't support API-based models now but you could train your model with the GPT cache we provided: https://github.com/Pinafore/nlp-hw/tree/master/models.
+
+I have no ideas why my model is not working. Could you help me?
+- Yes! After you model submission is evaluated, you could check the first few example details with how scores are calculated [here](https://huggingface.co/datasets/umdclip/qanta_leaderboard_logs)!
 """
 
 EVALUATION_QUEUE_TEXT = """
@@ -110,7 +113,7 @@ qa_pipe(question=“Where is UMD?”, context=”UMD is in Maryland.”)
 
 (4) `Precision` by default is `float16`. You could update it as needed.
 
-(5) If you have a trained retriever and want to submit an Extractive QA system, please also fill in the `Retrieved dataset name` and `Retriever model`.
+(5) You could leave the `Retrieved dataset name` and `Retriever model` fields empty as we provide context for your extractive QA model. Let us know if you want to use your own context or retriver via an email!
 
 Here is a tutorial on how you could make pipe wrappers for submissions: [Colab](https://colab.research.google.com/drive/1bCt2870SdY6tI4uE3JPG8_3nLmNJXX6_?usp=sharing)
 """