[BLOCK-MAP] 1k CHECKPOINTS (SAVE TO F-DRIVE)
[SIGNAL ANALYSIS] CAGS GRADIENT SURGERY & PEAK DETECTION
This tool visualizes the authentic training progress of JamOne Nano on a standard PC without GPU acceleration. The data is parsed directly from the verified testlog.txt.
Blue Markers: Represent the 1,000-step intervals where model checkpoints are committed to the F-Drive using memory mapping.
Yellow Peaks (e.g., Step 3820): Highlight moments where the loss spiked (reaching 5.35). During these events, the Adaptive Gradient Surgery (CAGS) intervention successfully stabilized the model, preventing divergence during CPU-only training.