| NAME: SEnSeIv2-SegFormerB2-alldata-ambiguous | |
| #------------- | |
| # Model options | |
| #------------- | |
| PATCH_SIZE: 512 | |
| SEnSeIv2: 'hf_models/sensei-configs/senseiv2-medium.yaml' | |
| MODEL_TYPE: 'Segformer' | |
| SEGFORMER_CONFIG: 'nvidia/mit-b2' | |
| RECOVERY_MODULE: false | |
| CLASSES: 7 | |
| MULTIMODAL: false | |
| NUM_CHANNELS: null # Set to null for sensor independent models | |
| #---------------- | |
| # Training options (not needed for inference) | |
| #---------------- | |
| EPOCHS: 105 | |
| BATCH_SIZE: 8 | |
| PHASES: [0, 1, 2, 75, 95, 110] | |
| ACCUMULATE_STEPS: [1, 1, 1, 1, 1, 1] | |
| LR: [0.000005, 0.00002, 0.0001, 0.00002, 0.00001, 0.000002] | |
| EPSILON: 0.000001 | |
| WEIGHT_DECAY: 0.0001 | |
| L1_REG: 0 | |
| RECOVERY_WARMUP_STEPS: 10000 | |
| RECOVERY_LOSS_FACTOR: 1 | |
| LOSS: 'ambiguous_crossentropy_loss' | |
| #------------- | |
| # Data options | |
| # Note: L7Irish and L8CCA are very large, so repeat other datasets to make up for it | |
| # Training epochs will max out at 4000 steps, so repeating datasets beyond that just | |
| # changes relative frequency of each dataset appearing. | |
| #------------- | |
| TRAIN_DIRS: | |
| - 'path/to/be/set1' # Multiple paths to different datasets | |
| - 'path/to/be/set2' | |
| - 'path/to/be/set3' | |
| - 'path/to/be/set4' | |
| VALID_DIRS: | |
| - 'path/to/be/set' | |
| MIN_BANDS: 3 | |
| MAX_BANDS: 13 |