Allegro-MP-L
Predictions
Convex hull distance prediction errors projected onto elements
2 He 0
10 Ne 0
18 Ar 0
36 Kr 0
54 Xe 0.004
57 La 0.0722
58 Ce 0.066
59 Pr 0.0704
60 Nd 0.0705
61 Pm 0.0527
62 Sm 0.0717
63 Eu 0.0825
64 Gd 0.0824
65 Tb 0.0756
66 Dy 0.0798
67 Ho 0.0763
68 Er 0.0796
69 Tm 0.0809
70 Yb 0.0737
71 Lu 0.0762
86 Rn 0
89 Ac 0.0584
90 Th 0.1
91 Pa 0.112
92 U 0.103
93 Np 0.15
94 Pu 0.333
95 Am 0
96 Cm 0
97 Bk 0
98 Cf 0
99 Es 0
100 Fm 0
101 Md 0
102 No 0
103 Lr 0
118 Og 0
57-71 La-Lu Lanthanides
89-103 Ac-Lr Actinides
Trained By
Model Info
- Model Version 0.1
- Model Type UIP
- Targets EFSG
- Openness OSOD
- Train Task S2EFS
- Test Task IS2RE-SR
- Trained for Benchmark Yes
Training Set
MPtrj: 1.58M structures from 146k materials
Description
Large 'compliant' Allegro foundation potential; see https://www.nequip.net/models/mir-group/Allegro-MP-L:0.1 for details and https://arxiv.org/abs/2504.16068 for model/training infrastructure.
Steps
Single training run on MPtrj with specified parameters.
Hyperparameters
- max_force:
0.05 - max_steps:
500 - ase_optimizer:
"GOQN" - cell_filter:
"FrechetCellFilter" - optimizer:
"AdamW" - weight_decay:
0.001 - graph_construction_radius:
6 - sph_harmonics_l_max:
3 - n_layers:
5 - n_features:
96 - parity:
false - zbl_potential:
false - allegro_mlp_depth:
3 - allegro_mlp_width:
1024 - tensor_path_channel_coupling:
true - polynomial_cutoff:
8 - n_radial_bessel_basis:
12 - loss:
"Huber - delta=0.01 for energy, delta=0.1 for stress, stratified delta (0.01, 0.007, 0.004, 0.001) for force" - loss_weights:
{"energy":1,"force":5,"stress":0.01} - batch_size:
520 - initial_learning_rate:
0.01 - gradient_clip_val:
0.015 - learning_rate_schedule:
"ReduceLROnPlateau - factor=0.5, patience=250, min_lr=1e-6" - epochs:
250 - max_neighbors:
null