This pipeline combines two search methods: a fast approximate search and a precise exact search. It first narrows down options quickly, then carefully picks the best match. This helps find answers faster and more accurately.
Loss
1.0 | *
0.8 | *
0.6 | *
0.4 | *
0.2 | *
0.0 +---------
1 2 3 4 5 Epochs| Epoch | Loss ↓ | Accuracy ↑ | Observation |
|---|---|---|---|
| 1 | 0.85 | 0.60 | Initial training with random weights, loss high, accuracy moderate |
| 2 | 0.65 | 0.72 | Model learns basic patterns, loss decreases, accuracy improves |
| 3 | 0.50 | 0.80 | Better ranking ability, loss continues to drop, accuracy rises |
| 4 | 0.40 | 0.85 | Model converging, loss lower, accuracy higher |
| 5 | 0.35 | 0.88 | Training stabilizes, good balance of speed and precision |