PrithviEO / conf /config.yaml
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seed: 42
data:
root: data
format_version: prithvi_eo_2_synthetic_engineering_v1
train_samples: 4
test_samples: 2
channels: 6
frames: 4
image_size: 224
band_names: [Blue, Green, Red, Narrow_NIR, SWIR1, SWIR2]
band_codes: [B02, B03, B04, B8A, B11, B12]
mean: [1087.0, 1342.0, 1433.0, 2734.0, 1958.0, 1363.0]
std: [2248.0, 2179.0, 2178.0, 1850.0, 1242.0, 1049.0]
model:
input_size: [4, 224, 224]
patch_size: [1, 16, 16]
channels: 6
mask_ratio: 0.75
encoder_dim: 96
encoder_depth: 2
encoder_heads: 4
decoder_dim: 64
decoder_depth: 1
decoder_heads: 4
mlp_ratio: 4
metadata_dropout: 0.1
norm_pix_loss: false
paper_model_300M_TL:
input_size: [4, 224, 224]
patch_size: [1, 16, 16]
encoder_dim: 1024
encoder_depth: 24
encoder_heads: 16
decoder_dim: 512
decoder_depth: 8
decoder_heads: 16
parameter_count: 300M
paper_model_600M_TL:
input_size: [4, 224, 224]
patch_size: [1, 14, 14]
encoder_dim: 1280
encoder_depth: 32
encoder_heads: 16
decoder_dim: 512
decoder_depth: 8
decoder_heads: 16
parameter_count: 600M
paper_training:
samples: 4.2M
validation_samples: 46k
epochs: 400
global_batch_size: 3840
maximum_learning_rate: 0.0005
warmup_epochs: 40
weight_decay: 0.05
train:
epochs: 1
batch_size: 2
learning_rate: 0.0005
weight_decay: 0.000001
num_workers: 0
runtime:
device: auto
paths:
checkpoint: result/checkpoints/prithvi_eo.pt
training_metrics: result/training/metrics.json
inference_dir: result/output
evaluation_dir: result/evaluation