| { |
| "model_id": "MatterWaveAI/grt-30m-chat", |
| "architecture": "GRTForCausalLM", |
| "parameters": 29305498, |
| "nn_linear_layers": 0, |
| "chat_template": "ChatML (<|im_start|> / <|im_end|>)", |
| "before_sft": { |
| "val_loss": 5.2083, |
| "val_ppl": 182.7854, |
| "assistant_token_acc": 0.2469, |
| "assistant_response_margin": 0.4397, |
| "multiturn_val_loss": 5.348, |
| "multiturn_val_ppl": 210.1897 |
| }, |
| "after_sft": { |
| "val_loss": 0.2904, |
| "val_ppl": 1.337, |
| "pair_adam_100step_val_loss": 0.3129, |
| "pair_adam_100step_val_ppl": 1.3674, |
| "assistant_token_acc": 0.9988, |
| "assistant_response_margin": 1.0754, |
| "multiturn_val_loss": 1.7855, |
| "multiturn_val_ppl": 5.9628, |
| "samples": [ |
| { |
| "user": "Can you explain this briefly? What is GRT-30M?", |
| "target": "GRT-30M is a 29.3M-parameter Givens Rotational Transformer developed by MatterWave AI that replaces every dense nn.Linear matrix with cascaded 2D Givens rotations and butterfly permutations.", |
| "generated": "GRT-30M is a 29.3M-parameter Givens Rotational Transformer developed by MatterWave AI that replaces every dense nn.Linear matrix with cascaded 2D Givens rotations and butterfly permutations." |
| }, |
| { |
| "user": "Can you explain this briefly? How does a Givens Rotational Transformer replace dense linear layers?", |
| "target": "Instead of O(D^2) dense matrix multiplications, GRT represents hidden states as planar coordinate pairs and transforms them through butterfly-permuted 2D Givens rotations modulated by Clifford algebra features.", |
| "generated": "Instead of O(D^2) dense matrix multiplications, GRT represents hidden states as planar coordinate pairs and transforms them through butterfly-permuted 2D Givens rotations modulated by Clifford algebra features." |
| }, |
| { |
| "user": "Can you explain this briefly? What is PearlNorm in the GRT architecture?", |
| "target": "PearlNorm is a pair-aware RMS normalization layer that divides each planar (x, y) pair by the root-mean-square of pair radii, rescaling magnitudes while preserving every pair's phase angle.", |
| "generated": "PearlNorm is a pair-aware RMS normalization layer that divides each planar (x, y) pair by the root-mean-square of pair radii, rescaling magnitudes while preserving every pair's phase angle." |
| }, |
| { |
| "user": "Can you explain this briefly? What is RadialGELU?", |
| "target": "RadialGELU applies a GELU activation to the Euclidean radius r of each 2D coordinate pair as gelu(r) / r, introducing nonlinearity on pair magnitudes without distorting phase directions.", |
| "generated": "RadialGELU applies a GELU activation to the Euclidean radius r of each 2D coordinate pair as gelu(r) / r, introducing nonlinearity on pair magnitudes without distorting phase directions." |
| }, |
| { |
| "user": "Can you explain this briefly? How are token embeddings parameterized in GRT?", |
| "target": "Each token in GRTEmbedding is stored as hidden_size // 2 phase angles plus a scalar log-magnitude, emitting exp(log_magnitude) * (cos(theta), sin(theta)) on the hypersphere.", |
| "generated": "Each token in GRTEmbedding is stored as hidden_size // 2 phase angles plus a scalar log-magnitude, emitting exp(log_magnitude) * (cos(theta), sin(theta)) on the hypersphere." |
| } |
| ] |
| }, |
| "optimizer_ablations_8way": { |
| "hessian_pair_adam": { |
| "variant": "HessianPairAdam (Sophia-Torus Cauchy-Riemann Curvature)", |
| "final_train_loss": 0.9501, |
| "val_loss": 0.2904, |
| "val_ppl": 1.337, |
| "assistant_token_acc": 0.9988, |
| "assistant_response_margin": 1.0754, |
| "assistant_response_seq_margin": 32.9186, |
| "multiturn_val_loss": 1.7855, |
| "multiturn_val_ppl": 5.9628, |
| "multiturn_token_acc": 0.8026, |
| "step100_val_loss": 0.3522, |
| "step100_val_ppl": 1.4222, |
| "elapsed_s": 49.51 |
| }, |
| "cyclide_adam": { |
| "variant": "CyclideAdam (Dupin Cyclide Conic Metric + Deviatoric Twist)", |
| "final_train_loss": 0.9506, |
| "val_loss": 0.2932, |
| "val_ppl": 1.3406, |
| "assistant_token_acc": 0.9988, |
| "assistant_response_margin": 0.9446, |
| "assistant_response_seq_margin": 28.0276, |
| "multiturn_val_loss": 1.9591, |
| "multiturn_val_ppl": 7.0933, |
| "multiturn_token_acc": 0.7487, |
| "step100_val_loss": 0.3522, |
| "step100_val_ppl": 1.4222, |
| "elapsed_s": 50.19 |
| }, |
| "pair_adam": { |
| "variant": "PairAdam (Factored Toroidal Baseline)", |
| "final_train_loss": 0.9505, |
| "val_loss": 0.2971, |
| "val_ppl": 1.346, |
| "assistant_token_acc": 0.9988, |
| "assistant_response_margin": 1.0982, |
| "assistant_response_seq_margin": 32.9333, |
| "multiturn_val_loss": 2.0593, |
| "multiturn_val_ppl": 7.8407, |
| "multiturn_token_acc": 0.7385, |
| "step100_val_loss": 0.3639, |
| "step100_val_ppl": 1.439, |
| "elapsed_s": 48.57 |
| }, |
| "huygens_adam": { |
| "variant": "HuygensAdam (Circular Order Parameter R_p Splay Torque)", |
| "final_train_loss": 0.9498, |
| "val_loss": 0.3107, |
| "val_ppl": 1.3644, |
| "assistant_token_acc": 1.0, |
| "assistant_response_margin": 1.0257, |
| "assistant_response_seq_margin": 30.9379, |
| "multiturn_val_loss": 1.6645, |
| "multiturn_val_ppl": 5.2829, |
| "multiturn_token_acc": 0.8154, |
| "step100_val_loss": 0.3784, |
| "step100_val_ppl": 1.4599, |
| "elapsed_s": 67.79 |
| }, |
| "huygens_symplectic_adam": { |
| "variant": "HuygensSymplecticAdam (Two-Stage Huygens -> Symplectic Curriculum)", |
| "final_train_loss": 0.9502, |
| "val_loss": 0.3361, |
| "val_ppl": 1.3995, |
| "assistant_token_acc": 0.9988, |
| "assistant_response_margin": 1.0957, |
| "assistant_response_seq_margin": 31.8603, |
| "multiturn_val_loss": 1.7592, |
| "multiturn_val_ppl": 5.8075, |
| "multiturn_token_acc": 0.8051, |
| "step100_val_loss": 0.398, |
| "step100_val_ppl": 1.4889, |
| "elapsed_s": 65.69 |
| }, |
| "symplectic_adam": { |
| "variant": "SymplecticAdam (Gromov-Liouville Non-Squeezing Floor + Casimir Cavity)", |
| "final_train_loss": 0.9502, |
| "val_loss": 0.3441, |
| "val_ppl": 1.4108, |
| "assistant_token_acc": 0.9938, |
| "assistant_response_margin": 1.1464, |
| "assistant_response_seq_margin": 34.5992, |
| "multiturn_val_loss": 1.9487, |
| "multiturn_val_ppl": 7.0199, |
| "multiturn_token_acc": 0.7513, |
| "step100_val_loss": 0.3961, |
| "step100_val_ppl": 1.4859, |
| "elapsed_s": 50.95 |
| }, |
| "gyric_adam": { |
| "variant": "GyricAdam (Poinsot-Lande Gyroscopic Projection + Thomas Precession)", |
| "final_train_loss": 0.9503, |
| "val_loss": 0.3476, |
| "val_ppl": 1.4157, |
| "assistant_token_acc": 0.9975, |
| "assistant_response_margin": 1.0779, |
| "assistant_response_seq_margin": 32.9217, |
| "multiturn_val_loss": 1.8009, |
| "multiturn_val_ppl": 6.0552, |
| "multiturn_token_acc": 0.7718, |
| "step100_val_loss": 0.4194, |
| "step100_val_ppl": 1.5211, |
| "elapsed_s": 70.5 |
| }, |
| "polar_natural_adam": { |
| "variant": "PolarNaturalAdam (Riemannian Polar Metric + Cauchy-Riemann Hessian)", |
| "final_train_loss": 0.9521, |
| "val_loss": 0.3883, |
| "val_ppl": 1.4745, |
| "assistant_token_acc": 0.9913, |
| "assistant_response_margin": 0.9159, |
| "assistant_response_seq_margin": 27.5035, |
| "multiturn_val_loss": 1.8642, |
| "multiturn_val_ppl": 6.4505, |
| "multiturn_token_acc": 0.7692, |
| "step100_val_loss": 0.4398, |
| "step100_val_ppl": 1.5524, |
| "elapsed_s": 49.4 |
| } |
| } |
| } |
|
|
