Image Classification on MNIST (Accuracy, NLL, ECE, Brier)
99.63AccuracyEVON
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| EVONOptimizer=EVON, Monte Carlo samples (BMA)=32, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.63 | 0.026 | 1.49 | 0.007 | |
| EVONOptimizer=EVON, Monte Carlo samples (BMA)=1, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.6 | 0.027 | 0.95 | 0.007 | |
| SOAPOptimizer=SOAP, Monte Carlo samples (BMA)=1, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.55 | 0.035 | 0.85 | 0.008 | |
| IVONOptimizer=IVON, Monte Carlo samples (BMA)=32, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.53 | 0.032 | 1.09 | 0.008 | |
| IVONOptimizer=IVON, Monte Carlo samples (BMA)=1, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.52 | 0.033 | 1.07 | 0.008 | |
| AdamWOptimizer=AdamW, Monte Carlo samples (BMA)=1, Backbone=ViT-B/16, Pre-training=OpenAI CLIP, Fine-tuning protocol=linear layers (99% of parameters)2026.06 | 99.51 | 0.031 | 1.01 | 0.009 |