From 2b5c3a4d4cdc829c05b795f8ef8bb66ca98d1f27 Mon Sep 17 00:00:00 2001 From: Abhishek Das Date: Tue, 21 Nov 2023 11:29:33 -0800 Subject: [PATCH] Update EqV2 31M ODAC checkpoint (#599) * Adds link to updated EqV2 31M checkpoint * Minor updates to bibtex entries --- MODELS.md | 22 +++++++++++----------- configs/odac/s2ef/base.yml | 8 +------- configs/odac/s2ef/eqv2_31M.yml | 20 ++++++++++---------- 3 files changed, 22 insertions(+), 28 deletions(-) diff --git a/MODELS.md b/MODELS.md index d24b34dfe..f12b2f4c2 100644 --- a/MODELS.md +++ b/MODELS.md @@ -93,7 +93,7 @@ The Open Catalyst 2020 (OC20) dataset is licensed under a [Creative Commons Attr Please consider citing the following paper in any research manuscript using the OC20 dataset or pretrained models, as well as the original paper for each model: -``` +```bibtex @article{ocp_dataset, author = {Chanussot*, Lowik and Das*, Abhishek and Goyal*, Siddharth and Lavril*, Thibaut and Shuaibi*, Muhammed and Riviere, Morgane and Tran, Kevin and Heras-Domingo, Javier and Ho, Caleb and Hu, Weihua and Palizhati, Aini and Sriram, Anuroop and Wood, Brandon and Yoon, Junwoong and Parikh, Devi and Zitnick, C. Lawrence and Ulissi, Zachary}, title = {Open Catalyst 2020 (OC20) Dataset and Community Challenges}, @@ -126,12 +126,12 @@ The Open Catalyst 2022 (OC22) dataset is licensed under a [Creative Commons Attr Please consider citing the following paper in any research manuscript using the OC22 dataset or pretrained models, as well as the original paper for each model: -``` +```bibtex @article{oc22_dataset, author = {Tran*, Richard and Lan*, Janice and Shuaibi*, Muhammed and Wood*, Brandon and Goyal*, Siddharth and Das, Abhishek and Heras-Domingo, Javier and Kolluru, Adeesh and Rizvi, Ammar and Shoghi, Nima and Sriram, Anuroop and Ulissi, Zachary and Zitnick, C. Lawrence}, - title = {The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis}, - year = {2022}, - journal = {arXiv preprint arXiv:2206.08917}, + title = {The Open Catalyst 2022 (OC22) dataset and challenges for oxide electrocatalysts}, + journal = {ACS Catalysis}, + year={2023}, } ``` @@ -143,14 +143,14 @@ OC22 dataset or pretrained models, as well as the original paper for each model: |Model |Checkpoint | Config | |--- |--- |--- | -|Schnet | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Schnet.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/schnet.yml) | -|Dimenet++ | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/DimenetPP.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/dpp.yml) | +|SchNet | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Schnet.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/schnet.yml) | +|DimeNet++ | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/DimenetPP.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/dpp.yml) | |PaiNN | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/PaiNN.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/painn.yml) | -|Gemnet-OC | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Gemnet-OC.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/gemnet-oc.yml) | +|GemNet-OC | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Gemnet-OC.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/gemnet-oc.yml) | |eSCN | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/eSCN.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/eSCN.yml) | -|EquiformerV2 | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Equiformer_V2.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/eqv2_31M.yml) | +|EquiformerV2 | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231116/eqv2_31M.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/eqv2_31M.yml) | |EquiformerV2 (Large) | [checkpoint](https://dl.fbaipublicfiles.com/dac/checkpoints_20231018/Equiformer_V2_Large.pt) | [config](https://github.com/Open-Catalyst-Project/ocp/tree/main/configs/odac/s2ef/eqv2_153M.yml) | - + ## IS2RE Direct models |Model |Checkpoint | Config | @@ -163,7 +163,7 @@ The Open DAC 2023 (ODAC23) dataset is licensed under a [Creative Commons Attribu Please consider citing the following paper in any research manuscript using the ODAC23 dataset: -``` +```bibtex @article{odac23_dataset, author = {Anuroop Sriram and Sihoon Choi and Xiaohan Yu and Logan M. Brabson and Abhishek Das and Zachary Ulissi and Matt Uyttendaele and Andrew J. Medford and David S. Sholl}, title = {The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture}, diff --git a/configs/odac/s2ef/base.yml b/configs/odac/s2ef/base.yml index 13decb368..52c8369df 100644 --- a/configs/odac/s2ef/base.yml +++ b/configs/odac/s2ef/base.yml @@ -13,13 +13,7 @@ logger: name: wandb task: - dataset: trajectory_lmdb - description: "Regressing to energies and forces for DFT trajectories from ODAC" - type: regression - metric: mae - labels: - - potential energy - grad_input: atomic forces + dataset: lmdb train_on_free_atoms: True eval_on_free_atoms: True primary_metric: forces_mae diff --git a/configs/odac/s2ef/eqv2_31M.yml b/configs/odac/s2ef/eqv2_31M.yml index 49b965f54..3b9063552 100644 --- a/configs/odac/s2ef/eqv2_31M.yml +++ b/configs/odac/s2ef/eqv2_31M.yml @@ -45,12 +45,12 @@ model: weight_init: 'uniform' # ['uniform', 'normal'] - norm_scale_nodes: 192.561 - norm_scale_degree: 21.024127419363214 # Radius = 12, MaxNbrs = 20 + avg_num_nodes: 192.561 + avg_degree: 21.024127419363214 optim: - batch_size: 6 # 6 - eval_batch_size: 4 # 6 + batch_size: 1 + eval_batch_size: 1 grad_accumulation_steps: 1 # gradient accumulation: effective batch size = `grad_accumulation_steps` * `batch_size` * (num of GPUs) load_balancing: atoms num_workers: 8 @@ -58,20 +58,20 @@ optim: optimizer: AdamW optimizer_params: - weight_decay: 0.2 + weight_decay: 0.3 scheduler: LambdaLR scheduler_params: lambda_type: cosine warmup_factor: 0.2 warmup_epochs: 0.01 - lr_min_factor: 0.01 + lr_min_factor: 0.01 - max_epochs: 1 - force_coefficient: 100 - energy_coefficient: 4 + max_epochs: 3 + force_coefficient: 200 + energy_coefficient: 1 clip_grad_norm: 100 ema_decay: 0.999 loss_energy: mae loss_force: l2mae - eval_every: 2500 # 5000 + eval_every: 5000