evalstate/tiny-memorization-results
Tiny memorization experiment results Per-run learning curves (loss_curve.csv: step, epoch, lr, train_loss_bits, held_loss_bits), final metrics (metrics.json including memorized bits, bits/parameter, L_train, L_held), and raw state.pt checkpoints for every run. Aggregated summary.csv/summary.json and figures (capacity_plot.png, loss_curves.png) are at the repo root. Memorization metric (paper Sec 3.2): mem = N_data_tokens * (log2 V - L_train_bits); bits_per_param = mem /… See the full description on the dataset page: https://huggingface.co/datasets/evalstate/tiny-memorization-results.
Tiny memorization experiment results
Per-run learning curves (loss_curve.csv: step, epoch, lr, trainlossbits, heldlossbits), final metrics (metrics.json including memorized bits, bits/parameter, Ltrain, Lheld), and raw state.pt checkpoints for every run. Aggregated summary.csv/summary.json and figures (capacity_plot.png, loss_curves.png) are at the repo root.
Memorization metric (paper Sec 3.2): mem = N_data_tokens * (log2 V - L_train_bits); bits_per_param = mem / n_params. Capacity ~ max memorization over dataset sizes.
