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diff --git a/training/conf/experiment/barlow_twins.yaml b/training/conf/experiment/barlow_twins.yaml
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-# @package _global_
-
-defaults:
- - override /criterion: null
- - override /datamodule: null
- - override /network: null
- - override /model: null
- - override /lr_schedulers: null
- - override /optimizers: null
-
-epochs: &epochs 1000
-summary: [[1, 1, 56, 1024]]
-
-criterion:
- _target_: text_recognizer.criterions.barlow_twins.BarlowTwinsLoss
- dim: 512
- lambda_: 3.9e-3
-
-callbacks:
- stochastic_weight_averaging:
- _target_: pytorch_lightning.callbacks.StochasticWeightAveraging
- swa_epoch_start: 0.75
- swa_lrs: 1.0e-5
- annealing_epochs: 10
- annealing_strategy: cos
- device: null
-
-optimizers:
- madgrad:
- _target_: madgrad.MADGRAD
- lr: 1.0e-3
- momentum: 0.9
- weight_decay: 1.0e-6
- eps: 1.0e-6
- parameters: network
-
-lr_schedulers:
- network:
- _target_: torch.optim.lr_scheduler.OneCycleLR
- max_lr: 3.0e-4
- total_steps: null
- epochs: *epochs
- steps_per_epoch: 45
- pct_start: 0.03
- anneal_strategy: cos
- cycle_momentum: true
- base_momentum: 0.85
- max_momentum: 0.95
- div_factor: 25
- final_div_factor: 1.0e4
- three_phase: false
- last_epoch: -1
- verbose: false
- # Non-class arguments
- interval: step
- monitor: val/loss
-
-datamodule:
- _target_: text_recognizer.data.iam_lines.IAMLines
- batch_size: 16
- num_workers: 12
- train_fraction: 0.9
- pin_memory: false
- transform: transform/iam_lines_barlow.yaml
- test_transform: transform/iam_lines_barlow.yaml
- mapping:
- _target_: text_recognizer.data.mappings.emnist_mapping.EmnistMapping
-
-network:
- _target_: text_recognizer.networks.barlow_twins.network.BarlowTwins
- encoder:
- _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
- arch: b0
- out_channels: 1280
- stochastic_dropout_rate: 0.2
- bn_momentum: 0.99
- bn_eps: 1.0e-3
- projector:
- _target_: text_recognizer.networks.barlow_twins.projector.Projector
- dims: [1280, 512, 512, 512]
-
-model:
- _target_: text_recognizer.models.barlow_twins.BarlowTwinsLitModel
-
-trainer:
- _target_: pytorch_lightning.Trainer
- stochastic_weight_avg: true
- auto_scale_batch_size: binsearch
- auto_lr_find: false
- gradient_clip_val: 0.0
- fast_dev_run: false
- gpus: 1
- precision: 16
- max_epochs: *epochs
- terminate_on_nan: true
- weights_summary: null
- limit_train_batches: 1.0
- limit_val_batches: 1.0
- limit_test_batches: 1.0
- resume_from_checkpoint: null
- accumulate_grad_batches: 32
- overfit_batches: 0