mars-aurora-openmars-random-init
Aurora architecture trained on OpenMARS from random initialization for comparison with pretrained fine-tuning.
This repository contains model-only weights exported from an OpenMARS fine-tuned
Aurora checkpoint. Optimizer state and RNG state were intentionally stripped.
Source checkpoint
artifacts/openmars_runs/20260621_000248_random_init_a6000_6gpu_bs20_e10/checkpoint_step_9158.pt
Training configuration
- Model size:
base
- Split manifest:
splits/openmars_my28-34_train_my35_val.json
- Epochs:
13
- Batch size per GPU:
20
- Base LR:
0.0001
- New/Mars LR:
0.0001
- Resume checkpoint:
artifacts/openmars_runs/20260621_000248_random_init_a6000_6gpu_bs12_e10/checkpoint_step_7760.pt
Loading
Use this repository with the mars_weather.make_mars_aurora helper from the
project code. Load openmars_stats.json, construct the configured Mars Aurora
model, and then load model.safetensors or pytorch_model.bin as a state dict.
