DialoGPT- cannot increase number of conversation turns
Author: albusdemens
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 3.5.1
- Platform: Linux-5.4.0-58-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.6.13
- PyTorch version (GPU?): 1.7.1 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
@patrickvonplaten @LysandreJik

## Information

Model I am using (Bert, XLNet ...): DialoGPT

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

I fine-tuned DialoGPT on some sitcom subtitles, and now I am trying to chat with it using the commands listed [here](https://gist.github.com/albusdemens/9cd5602f088720e403f84038e088d696) (in the example, I use the Microsoft fine-tuned model).  

1. When I increase the number of conversation turns from 5 to 10, everything goes OK with the Microsoft model. 
2. If I increase the number of conversation turns to 10 using my fine-tuned model, reply number six is something like 

```
>> User:hello
OurBot: Hello.
>> User:how are things?
OurBot: They're fine.
>> User:cool. Did you have lunch already?
OurBot: I did, actually.
>> User:what did you have?
OurBot: Oh, um, i just wanted to toast.
>> User:where?
**OurBot: !!!hello!**
```

## Expected behavior

Using the DialoGPT model I fine-tuned, I would like to be able to have the same number of turns that I have using the Microsoft model. 


Comments:
Hey @albusdemens,

Sorry I don't follow here completely. Does the model crash after 6 turns or does it just give a qualitatively bad answer?

Hey @patrickvonplaten, the second option (the quality of the answers is noticeably worse). Often I get outputs like `?!!`, `!.!!?!?` and similar. Usually low quality outputs don't show up in the first 3-4 conversation turns. When I use the Microsoft model instead, I don't get low-quality results after a few conversation turns. 

 Is there a way I can fix this?

This sounds very much like the model wasn't trained on long conversations to me...I'm not sure whether it's possible to enforce better quality without retraining the model

Thanks for your reply! Besides improving the quality of the training data,
do you think I should also increase the number of epochs?

On Tue, Mar 30, 2021, 6:15 AM Patrick von Platen ***@***.***>
wrote:

> This sounds very much like the model wasn't trained on long conversations
> to me...I'm not sure whether it's possible to enforce better quality
> without retraining the model
>
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