aliFrancis
commited on
Commit
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Parent(s):
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Add models
Browse files- full-models/SEnSeIv2-DeepLabv3-S2-unambiguous/config.yaml +37 -0
- full-models/SEnSeIv2-DeepLabv3-S2-unambiguous/weights.pt +3 -0
- full-models/SEnSeIv2-SegFormerB2-S2-ambiguous/config.yaml +39 -0
- full-models/SEnSeIv2-SegFormerB2-S2-ambiguous/weights.pt +3 -0
- full-models/SEnSeIv2-SegFormerB2-alldata-ambiguous/config.yaml +66 -0
- full-models/SEnSeIv2-SegFormerB2-alldata-ambiguous/weights.pt +3 -0
- full-models/SegFormerB2-S2-unambiguous/config.yaml +38 -0
- full-models/SegFormerB2-S2-unambiguous/weights.pt +3 -0
- sensei-configs/recovery-module.yaml +6 -0
- sensei-configs/senseiv2-medium.yaml +36 -0
full-models/SEnSeIv2-DeepLabv3-S2-unambiguous/config.yaml
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NAME: SEnSeIv2-DeepLabv3-S2-unambiguous
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#-------------
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# Model options
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#-------------
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PATCH_SIZE: 512
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SEnSeIv2: 'models/sensei-configs/senseiv2-medium.yaml'
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MODEL_TYPE: 'DeepLabv3+'
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DEEPLAB_CONFIG: 'resnet50'
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RECOVERY_MODULE: false
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CLASSES: 4
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MULTIMODAL: false
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NUM_CHANNELS: null # Set to null for sensor independent models
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#----------------
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#training options (not needed for inference)
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#----------------
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EPOCHS: 70
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BATCH_SIZE: 8
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PHASES: [0, 1, 2, 45, 60, 65]
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ACCUMULATE_STEPS: [1, 1, 1, 1, 4, 8]
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LR: [0.000005, 0.00002, 0.0001, 0.00001, 0.00001, 0.000002]
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EPSILON: 0.000001
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WEIGHT_DECAY: 0.0001
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L1_REG: 0
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RECOVERY_WARMUP_STEPS: 5000
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RECOVERY_LOSS_FACTOR: 1
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LOSS: 'ambiguous_crossentropy_loss'
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#Data options
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TRAIN_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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VALID_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/valid'
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MIN_BANDS: 3
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MAX_BANDS: 13
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full-models/SEnSeIv2-DeepLabv3-S2-unambiguous/weights.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:96c36be3b6dc2da504dc3f96cdc4006cd8ee29bff48a8a50c783730404388ecd
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size 109219821
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full-models/SEnSeIv2-SegFormerB2-S2-ambiguous/config.yaml
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NAME: SEnSeIv2-SegFormerB2-S2-ambiguous
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#-------------
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#Model options
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#-------------
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PATCH_SIZE: 512
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SEnSeIv2: 'models/sensei-configs/senseiv2-medium.yaml'
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MODEL_TYPE: 'Segformer'
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SEGFORMER_CONFIG: 'nvidia/mit-b2'
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RECOVERY_MODULE: false
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CLASSES: 7
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MULTIMODAL: false
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NUM_CHANNELS: null # Set to null for sensor independent models
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#----------------
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#training options (not needed for inference)
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#----------------
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EPOCHS: 105
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BATCH_SIZE: 8
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PHASES: [0, 1, 2, 75, 95, 110]
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ACCUMULATE_STEPS: [1, 1, 1, 1, 1, 1]
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LR: [0.000005, 0.00002, 0.0001, 0.00002, 0.00001, 0.000002]
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EPSILON: 0.000001
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WEIGHT_DECAY: 0.0001
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L1_REG: 0
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RECOVERY_WARMUP_STEPS: 10000
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RECOVERY_LOSS_FACTOR: 1
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LOSS: 'ambiguous_crossentropy_loss'
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# Data options
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# Note: L7Irish and L8CCA are very large, so repeat other datasets to make up for it
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# Training epochs will max out at 4000 steps, so repeating datasets beyond that just
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# changes relative frequency of each dataset appearing.
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TRAIN_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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VALID_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/valid'
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MIN_BANDS: 3
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MAX_BANDS: 13
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full-models/SEnSeIv2-SegFormerB2-S2-ambiguous/weights.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:215580a6f516714705cf26319eba3da824cab6a67a5972cc5ae5816aa5148ceb
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size 111716650
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full-models/SEnSeIv2-SegFormerB2-alldata-ambiguous/config.yaml
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NAME: SEnSeIv2-SegFormerB2-alldata-ambiguous
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#-------------
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# Model options
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#-------------
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PATCH_SIZE: 512
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SEnSeIv2: 'models/sensei-configs/senseiv2-medium.yaml'
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MODEL_TYPE: 'Segformer'
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SEGFORMER_CONFIG: 'nvidia/mit-b2'
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RECOVERY_MODULE: false
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CLASSES: 7
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MULTIMODAL: false
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NUM_CHANNELS: null # Set to null for sensor independent models
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#----------------
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# Training options (not needed for inference)
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#----------------
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EPOCHS: 105
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BATCH_SIZE: 8
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PHASES: [0, 1, 2, 75, 95, 110]
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ACCUMULATE_STEPS: [1, 1, 1, 1, 1, 1]
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LR: [0.000005, 0.00002, 0.0001, 0.00002, 0.00001, 0.000002]
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EPSILON: 0.000001
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WEIGHT_DECAY: 0.0001
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L1_REG: 0
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RECOVERY_WARMUP_STEPS: 10000
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RECOVERY_LOSS_FACTOR: 1
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LOSS: 'ambiguous_crossentropy_loss'
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#-------------
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# Data options
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# Note: L7Irish and L8CCA are very large, so repeat other datasets to make up for it
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# Training epochs will max out at 4000 steps, so repeating datasets beyond that just
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# changes relative frequency of each dataset appearing.
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#-------------
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TRAIN_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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- '/home/ali/data/cloud-masking/processed/S2CS12/train' # Repeat to boost sampling frequency
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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- '/home/ali/data/cloud-masking/processed/S2IRIS'
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- '/home/ali/data/cloud-masking/processed/S2IRIS'
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- '/home/ali/data/cloud-masking/processed/S2IRIS'
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- '/home/ali/data/cloud-masking/processed/S2IRIS'
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- '/home/ali/data/cloud-masking/processed/S2IRIS'
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- '/home/ali/data/cloud-masking/processed/S2KZ/train'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS-60m'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS-60m'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS-60m'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS-60m'
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- '/home/ali/data/cloud-masking/processed/L8SPARCS-60m'
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- '/home/ali/data/cloud-masking/processed/L8CCA'
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- '/home/ali/data/cloud-masking/processed/L7Irish'
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- '/home/ali/data/cloud-masking/processed/CP2'
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VALID_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/valid'
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MIN_BANDS: 3
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MAX_BANDS: 13
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full-models/SEnSeIv2-SegFormerB2-alldata-ambiguous/weights.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:f43a0c23eb4b22cf09c1c0d59fc3d2f050f164f7c1a43f18e4974458926c57d9
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size 111716650
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full-models/SegFormerB2-S2-unambiguous/config.yaml
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NAME: SegformerB2
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#-------------
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# Model options
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#-------------
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PATCH_SIZE: 512
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SEnSeIv2: false
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MODEL_TYPE: 'Segformer'
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SEGFORMER_CONFIG: 'nvidia/mit-b2'
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RECOVERY_MODULE: null
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MULTIMODAL: false
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NUM_CHANNELS: 13 # Set to null for sensor independent models
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CLASSES: 4
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#----------------
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# Training options (not needed for inference)
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#----------------
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EPOCHS: 60
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BATCH_SIZE: 8
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PHASES: [0, 1, 2, 40, 50, 55]
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ACCUMULATE_STEPS: [1, 1, 1, 1, 4, 8]
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LR: [0.000005, 0.00002, 0.0001, 0.00001, 0.00001, 0.000002]
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EPSILON: 0.000001
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WEIGHT_DECAY: 0.0001
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L1_REG: 0
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RECOVERY_WARMUP_STEPS: 0
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RECOVERY_LOSS_FACTOR: 0
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LOSS: 'ambiguous_crossentropy_loss' # Not actually ambiguous, because labels are not ambiguous
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#------------
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#Data options
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#------------
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TRAIN_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/train'
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VALID_DIRS:
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- '/home/ali/data/cloud-masking/processed/S2CS12/valid'
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MIN_BANDS: null
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MAX_BANDS: null
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full-models/SegFormerB2-S2-unambiguous/weights.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:a8378575b89c7dddf237edddb9981fa6c3cccc63490976884bf527eaaf9c191e
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size 109685259
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sensei-configs/recovery-module.yaml
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preconcatenation_layer_sizes:
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- 256
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- 32
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postconcatenation_layer_sizes:
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- 32
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sampling_rate: 10
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sensei-configs/senseiv2-medium.yaml
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---
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descriptors:
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style: SEnSeIv2
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N_embeddings: 32
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final_size: 74
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blocks:
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-
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type: GLOBAL_STATS
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percentiles:
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- 0.01
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- 0.1
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- 0.5
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- 0.9
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- 0.99
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-
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type: FCL
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layer_sizes:
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- 128
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- 128
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- 128
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skips: add
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-
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type: ATTENTION
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num_transformerencoders: 2
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intermediate_size: 256
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num_heads: 4
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dims_per_head: 32
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skips: true
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dropout: 0.2
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-
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type: BAND_EMBEDDING
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embedding_dims: 32 # number of output channels
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head_layer_sizes:
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- 128
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skips_heads: false
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normalize: true
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