OpenPhenom / config.json
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{
"_attn_implementation_autoset": true,
"apply_loss_unmasked": false,
"architectures": [
"MAEModel"
],
"crop_size": -1,
"decoder": {
"_target_": "mae_modules.CAMAEDecoder",
"depth": 8,
"embed_dim": 512,
"mlp_ratio": 4,
"norm_layer": {
"_partial_": true,
"_target_": "torch.nn.LayerNorm",
"eps": 1e-06
},
"num_heads": 16,
"num_modalities": 6,
"qkv_bias": true,
"tokens_per_modality": 256
},
"encoder": {
"_target_": "mae_modules.MAEEncoder",
"channel_agnostic": true,
"max_in_chans": 11,
"vit_backbone": {
"_target_": "vit.sincos_positional_encoding_vit",
"vit_backbone": {
"_target_": "vit.vit_small_patch16_256",
"global_pool": "avg"
}
}
},
"fourier_loss": {
"_target_": "loss.FourierLoss",
"num_multimodal_modalities": 6
},
"fourier_loss_weight": 0.0,
"input_norm": {
"_args_": [
{
"_target_": "normalizer.Normalizer"
},
{
"_target_": "torch.nn.InstanceNorm2d",
"affine": false,
"num_features": null,
"track_running_stats": false
}
],
"_target_": "torch.nn.Sequential"
},
"layernorm_unfreeze": true,
"loss": {
"_target_": "torch.nn.MSELoss",
"reduction": "none"
},
"lr_scheduler": {
"_partial_": true,
"_target_": "torch.optim.lr_scheduler.OneCycleLR",
"anneal_strategy": "cos",
"max_lr": 0.0001,
"pct_start": 0.1
},
"mask_fourier_loss": true,
"mask_ratio": 0.0,
"model_type": "MAE",
"norm_pix_loss": false,
"num_blocks_to_freeze": 0,
"optimizer": {
"_partial_": true,
"_target_": "timm.optim.lion.Lion",
"betas": [
0.9,
0.95
],
"lr": 0.0001,
"weight_decay": 0.05
},
"torch_dtype": "float32",
"transformers_version": "4.46.1",
"trim_encoder_blocks": null,
"use_MAE_weight_init": false
}