Yes, I ran some benchmarks. This architecture seems to match or beat Jev and Laya in all basic classification tasks (datasets tested: AG News, Emotion, MASSIVE Intent, Banking77)
The type of task in which it does really well, especially against Laya, is classification with >50 classes
But this architecture has no “reasoning”, so it performs rather poorly on tasks that require it, like the ones from the XLNI dataset (Jev/Laya do a lot better on this one)
For the latter cases, you could probably enhance the architecture with a lightweight LLM, something like a Gemma model. Or even some basic MLP
alt Hacker News
Yes, I ran some benchmarks. This architecture seems to match or beat Jev and Laya in all basic classification tasks (datasets tested: AG News, Emotion, MASSIVE Intent, Banking77)
The type of task in which it does really well, especially against Laya, is classification with >50 classes
But this architecture has no “reasoning”, so it performs rather poorly on tasks that require it, like the ones from the XLNI dataset (Jev/Laya do a lot better on this one)
For the latter cases, you could probably enhance the architecture with a lightweight LLM, something like a Gemma model. Or even some basic MLP