Everyone talks about deploying ML on edge devices. Very few people show what happens when you actually try.
I ran a full benchmark of four lightweight transformer models - DistilBERT, MobileBERT, TinyBERT-6L, and TinyBERT-4L — against traditional ML baselines on three real-world fault detection datasets.
The Setup
NASA C-MAPSS: Turbofan engine degradation (20,631 samples, 15% failure rate)
SECOM: Semiconductor manufacturing (1,567 samples, 6.6% failure rate)










