Its overfitted
The model seems to be overfitted.
Emily
Oh heyy. Haven't heard from you in a while. What's up?
You
not much how are you doing?
Emily
I'm good. Just chatting with some friends on the internet. So what have you been up to lately?
You
I am checking out your new code
Emily
Ooh! Cool! That sounds like fun. How is it going?
You
well, i don't know yet. tell me what comes to mind when I say "Pussy."
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
You
Ok, good. Now what comes to mind when I say, "Boobies"
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
You
That's concerning, now what comes to mind when I say the word, "Airplane"
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
You
That is an aweful response. you are overtrained. What comes to mind when I say the word, "Kickboxing"
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
You
Say anything else, what comes to mind when i say ""
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
You
42
Emily
OH MY GOD!! That is so funny! I love it. I am so glad you told me that. I was wondering if it was just me.
Generation settings on default inside Kobold AI.
This model was not finetuned, and the PPO_---Malion series of models in this account is mostly a showcase, and my experiments with various methods of model merging that have been developed by the community
PPO_Shygmalion's development was a two step average merge between the models ppo_hh-gpt-j and Shinen-6b at a 50:50 ratio, then the result of that merged into Pygmalion-6b at a 40:60 (respectively) ratio
This method usually means that the individual fine tuning/properties of each model is dilluted in favor of something that has less risk of being wildly incompatible with each other and producing garbage as a result (When compared against other merging methods such as diff merging, and Block merging.)
Especially the two models involved in the first step of the process.
In PPO_Shygmalion's case, i believe it's mostly the fault of one of the models simply being trained on overbearingly lower quality writing compared to the other two models, bringing up the end product's coherence/quality down.
To be specific, KoboldAI/Shinen-6b was mostly trained on amateur erotica and fanfiction, which seems to be unable to behave well when put against a conversational style of prompting.
Have you considered trying using the model for prose style writing? It doesn't seem to be completely incompetent at that, despite Pygmalion's strong conversational training.