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Diffstat (limited to 'training/conf/experiment/conv_perceiver_lines.yaml')
-rw-r--r-- | training/conf/experiment/conv_perceiver_lines.yaml | 76 |
1 files changed, 76 insertions, 0 deletions
diff --git a/training/conf/experiment/conv_perceiver_lines.yaml b/training/conf/experiment/conv_perceiver_lines.yaml new file mode 100644 index 0000000..26fe232 --- /dev/null +++ b/training/conf/experiment/conv_perceiver_lines.yaml @@ -0,0 +1,76 @@ +# @package _global_ + +defaults: + - override /criterion: cross_entropy + - override /callbacks: htr + - override /datamodule: iam_lines + - override /network: conv_perceiver + - override /model: lit_perceiver + - override /lr_scheduler: null + - override /optimizer: null + +tags: [lines, perceiver] +epochs: &epochs 260 +ignore_index: &ignore_index 3 +num_classes: &num_classes 57 +max_output_len: &max_output_len 89 +summary: [[1, 1, 56, 1024]] + +logger: + wandb: + tags: ${tags} + +criterion: + ignore_index: *ignore_index + # label_smoothing: 0.1 + +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 + +optimizer: + _target_: adan_pytorch.Adan + lr: 1.0e-4 + betas: [0.02, 0.08, 0.01] + weight_decay: 0.02 + +lr_scheduler: + _target_: torch.optim.lr_scheduler.ReduceLROnPlateau + mode: min + factor: 0.8 + patience: 10 + threshold: 1.0e-4 + threshold_mode: rel + cooldown: 0 + min_lr: 1.0e-5 + eps: 1.0e-8 + verbose: false + interval: epoch + monitor: val/cer + +datamodule: + batch_size: 8 + train_fraction: 0.95 + +network: + input_dims: [1, 1, 56, 1024] + num_classes: *num_classes + pad_index: *ignore_index + encoder: + depth: 5 + decoder: + depth: 6 + +model: + max_output_len: *max_output_len + +trainer: + gradient_clip_val: 1.0 + stochastic_weight_avg: true + max_epochs: *epochs + accumulate_grad_batches: 1 |