| --- |
| language: en |
| library_name: clinicadl |
| tags: |
| - clinicadl |
| license: mit |
| --- |
| # Model Card for None |
| This model was trained with ClinicaDL. You can find here the |
| ## General information |
| ## Architecture |
| This model was trained for **classification** and the architecture chosen is **Conv4_FC3**. |
| **dropout**: 0.0 |
| **latent_space_size**: 2 |
| **feature_size**: 1024 |
| **n_conv**: 4 |
| **io_layer_channels**: 8 |
| **recons_weight**: 1 |
| **kl_weight**: 1 |
| **normalization**: batch |
| **architecture**: Conv4_FC3 |
| **multi_network**: False |
| **dropout**: 0.0 |
| **latent_space_dimension**: 64 |
| **latent_space_size**: 2 |
| **selection_metrics**: ['loss'] |
| **label**: diagnosis |
| **selection_threshold**: 0.0 |
| **gpu**: True |
| **n_proc**: 32 |
| **batch_size**: 32 |
| **evaluation_steps**: 20 |
| **seed**: 0 |
| **deterministic**: False |
| **compensation**: memory |
| **transfer_path**: ../../autoencoders/exp3/maps |
| **transfer_selection_metric**: loss |
| **use_extracted_features**: False |
| **multi_cohort**: False |
| **diagnoses**: ['AD', 'CN'] |
| **baseline**: True |
| **normalize**: True |
| **data_augmentation**: False |
| **sampler**: random |
| **n_splits**: 5 |
| **epochs**: 200 |
| **learning_rate**: 1e-05 |
| **weight_decay**: 0.0001 |
| **patience**: 10 |
| **tolerance**: 0.0 |
| **accumulation_steps**: 1 |
| **optimizer**: Adam |
| **preprocessing_dict**: {'preprocessing': 't1-linear', 'mode': 'roi', 'use_uncropped_image': False, 'roi_list': ['leftHippocampusBox', 'rightHippocampusBox'], 'uncropped_roi': False, 'prepare_dl': False, 'file_type': {'pattern': '*space-MNI152NLin2009cSym_desc-Crop_res-1x1x1_T1w.nii.gz', 'description': 'T1W Image registered using t1-linear and cropped (matrix size 169×208×179, 1 mm isotropic voxels)', 'needed_pipeline': 't1-linear'}} |
| **mode**: roi |
| **network_task**: classification |
| **caps_directory**: $WORK/../commun/datasets/adni/caps/caps_v2021 |
| **tsv_path**: $WORK/Aramis_tools/ClinicaDL_tools/experiments_ADDL/data/ADNI/train |
| **validation**: KFoldSplit |
| **num_networks**: 2 |
| **label_code**: {'AD': 0, 'CN': 1} |
| **output_size**: 2 |
| **input_size**: [1, 50, 50, 50] |
| **loss**: None |
| |
