Update configs

5 files changed, 83 insertions, 67 deletions

diff --git a/training/conf/config.yaml b/training/conf/config.yaml
index f6118a9..fc06f7f 100644
--- a/training/conf/config.yaml
+++ b/training/conf/config.yaml
@@ -7,13 +7,11 @@ defaults:
   - datamodule: iam_extended_paragraphs
   - hydra: default
   - logger: wandb
-  - lr_schedulers:
-      - cosine_annealing
+  - lr_schedulers: cosine_annealing
   - mapping: characters
   - model: lit_transformer
   - network: conv_transformer
-  - optimizers:
-      - radam
+  - optimizers: radam
   - trainer: default
 
 seed: 4711
diff --git a/training/conf/experiment/conv_transformer_lines.yaml b/training/conf/experiment/conv_transformer_lines.yaml
index 38b13a5..260014c 100644
--- a/training/conf/experiment/conv_transformer_lines.yaml
+++ b/training/conf/experiment/conv_transformer_lines.yaml
@@ -30,37 +30,35 @@ callbacks:
     device: null
 
 optimizers:
-  radam:
-    _target_: torch.optim.RAdam
-    lr: 3.0e-4
-    betas: [0.9, 0.999]
-    weight_decay: 0
-    eps: 1.0e-8
-    parameters: network
+  _target_: torch.optim.RAdam
+  lr: 3.0e-4
+  betas: [0.9, 0.999]
+  weight_decay: 0
+  eps: 1.0e-8
+  parameters: network
 
 lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.OneCycleLR
-    max_lr: 3.0e-4
-    total_steps: null
-    epochs: *epochs
-    steps_per_epoch: 1284
-    pct_start: 0.3
-    anneal_strategy: cos
-    cycle_momentum: true
-    base_momentum: 0.85
-    max_momentum: 0.95
-    div_factor: 25.0
-    final_div_factor: 10000.0
-    three_phase: true
-    last_epoch: -1
-    verbose: false
-    interval: step
-    monitor: val/cer
+  _target_: torch.optim.lr_scheduler.OneCycleLR
+  max_lr: 3.0e-4
+  total_steps: null
+  epochs: *epochs
+  steps_per_epoch: 1354
+  pct_start: 0.3
+  anneal_strategy: cos
+  cycle_momentum: true
+  base_momentum: 0.85
+  max_momentum: 0.95
+  div_factor: 25.0
+  final_div_factor: 10000.0
+  three_phase: true
+  last_epoch: -1
+  verbose: false
+  interval: step
+  monitor: val/cer
 
 datamodule:
   batch_size: 8
-  train_fraction: 0.9
+  train_fraction: 0.95
 
 network:
   input_dims: [1, 1, 56, 1024]
diff --git a/training/conf/experiment/conv_transformer_paragraphs.yaml b/training/conf/experiment/conv_transformer_paragraphs.yaml
index 1465e62..7f0273f 100644
--- a/training/conf/experiment/conv_transformer_paragraphs.yaml
+++ b/training/conf/experiment/conv_transformer_paragraphs.yaml
@@ -10,13 +10,15 @@ defaults:
   - override /lr_schedulers: null
   - override /optimizers: null
 
-epochs: &epochs 629
+epochs: &epochs 600
+num_classes: &num_classes 58
 ignore_index: &ignore_index 3
+max_output_len: &max_output_len 682
 summary: [[1, 1, 576, 640], [1, 682]]
 
 criterion:
   ignore_index: *ignore_index
-  # label_smoothing: 0.1
+  label_smoothing: 0.05
 
 callbacks:
   stochastic_weight_averaging:
@@ -28,32 +30,52 @@ callbacks:
     device: null
 
 optimizers:
-  radam:
-    _target_: torch.optim.RAdam
-    lr: 1.5e-4
-    betas: [0.9, 0.999]
-    weight_decay: 0
-    eps: 1.0e-8
-    parameters: network
+  _target_: torch.optim.RAdam
+  lr: 3.0e-4
+  betas: [0.9, 0.999]
+  weight_decay: 0
+  eps: 1.0e-8
+  parameters: network
 
 lr_schedulers:
-  network:
-    _target_: torch.optim.lr_scheduler.ReduceLROnPlateau
-    mode: min
-    factor: 0.5
-    patience: 10
-    threshold: 1.0e-4
-    threshold_mode: rel
-    cooldown: 0
-    min_lr: 1.0e-6
-    eps: 1.0e-8
-    verbose: false
-    interval: epoch
-    monitor: val/loss
+  _target_: torch.optim.lr_scheduler.OneCycleLR
+  max_lr: 2.0e-4
+  total_steps: null
+  epochs: *epochs
+  steps_per_epoch: 3201
+  pct_start: 0.1
+  anneal_strategy: cos
+  cycle_momentum: true
+  base_momentum: 0.85
+  max_momentum: 0.95
+  div_factor: 25.0
+  final_div_factor: 10000.0
+  three_phase: true
+  last_epoch: -1
+  verbose: false
+  interval: step
+  monitor: val/cer
 
 datamodule:
   batch_size: 6
-  train_fraction: 0.9
+  train_fraction: 0.95
+
+network:
+  input_dims: [1, 1, 576, 640]
+  num_classes: *num_classes
+  pad_index: *ignore_index
+  encoder:
+    depth: 5
+  decoder:
+    depth: 6
+  pixel_embedding:
+    shape: [36, 40]
+
+model:
+  max_output_len: *max_output_len
 
 trainer:
+  gradient_clip_val: 0.5
   max_epochs: *epochs
+  accumulate_grad_batches: 1
+  resume_from_checkpoint: /home/aktersnurra/projects/text-recognizer/training/logs/runs/2022-06-16/21-00-39/checkpoints/last.ckpt
diff --git a/training/conf/lr_schedulers/cosine_annealing.yaml b/training/conf/lr_schedulers/cosine_annealing.yaml
index c53ee3a..e8364f0 100644
--- a/training/conf/lr_schedulers/cosine_annealing.yaml
+++ b/training/conf/lr_schedulers/cosine_annealing.yaml
@@ -1,8 +1,7 @@
-cosine_annealing:
-  _target_: torch.optim.lr_scheduler.CosineAnnealingLR
-  T_max: 256
-  eta_min: 0.0
-  last_epoch: -1
+_target_: torch.optim.lr_scheduler.CosineAnnealingLR
+T_max: 256
+eta_min: 0.0
+last_epoch: -1
 
-  interval: epoch
-  monitor: val/loss
+interval: epoch
+monitor: val/loss
diff --git a/training/conf/optimizers/radam.yaml b/training/conf/optimizers/radam.yaml
index 7ee1234..d11fcb5 100644
--- a/training/conf/optimizers/radam.yaml
+++ b/training/conf/optimizers/radam.yaml
@@ -1,7 +1,6 @@
-radam:
-  _target_: torch.optim.RAdam
-  lr: 1.5e-4
-  betas: [0.9, 0.999]
-  weight_decay: 1.0e-4
-  eps: 1.0e-8
-  parameters: network
+_target_: torch.optim.RAdam
+lr: 1.5e-4
+betas: [0.9, 0.999]
+weight_decay: 1.0e-4
+eps: 1.0e-8
+parameters: network