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authorGustaf Rydholm <gustaf.rydholm@gmail.com>2021-11-05 19:27:50 +0100
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2021-11-05 19:27:50 +0100
commit70540bf897df1d60375ea220cfab838cbd28c47f (patch)
tree67fac32a41c35f3e9d59a8c353fe27e8fd431eb2
parent194be7aa14744c2b5a9ef4e31ca19fb70ddfd775 (diff)
Update lines config
-rw-r--r--training/conf/experiment/conv_transformer_lines.yaml51
1 files changed, 18 insertions, 33 deletions
diff --git a/training/conf/experiment/conv_transformer_lines.yaml b/training/conf/experiment/conv_transformer_lines.yaml
index d2a666f..6ba4535 100644
--- a/training/conf/experiment/conv_transformer_lines.yaml
+++ b/training/conf/experiment/conv_transformer_lines.yaml
@@ -2,7 +2,7 @@
defaults:
- override /mapping: null
- - override /criterion: null
+ - override /criterion: cross_entropy
- override /callbacks: htr
- override /datamodule: iam_lines
- override /network: null
@@ -10,21 +10,18 @@ defaults:
- override /lr_schedulers: null
- override /optimizers: null
-epochs: &epochs 512
+epochs: &epochs 256
ignore_index: &ignore_index 3
-num_classes: &num_classes 58
+num_classes: &num_classes 57
max_output_len: &max_output_len 89
summary: [[1, 1, 56, 1024], [1, 89]]
criterion:
- _target_: text_recognizer.criterion.label_smoothing.LabelSmoothingLoss
- smoothing: 0.1
ignore_index: *ignore_index
mapping: &mapping
mapping:
_target_: text_recognizer.data.mappings.emnist.EmnistMapping
- # extra_symbols: [ "\n" ]
callbacks:
stochastic_weight_averaging:
@@ -38,31 +35,20 @@ callbacks:
optimizers:
madgrad:
_target_: madgrad.MADGRAD
- lr: 1.0e-4
+ lr: 3.0e-4
momentum: 0.9
- weight_decay: 5.0e-6
+ weight_decay: 0
eps: 1.0e-6
parameters: network
lr_schedulers:
network:
- _target_: torch.optim.lr_scheduler.OneCycleLR
- max_lr: 1.0e-4
- total_steps: null
- epochs: *epochs
- steps_per_epoch: 722
- pct_start: 0.01
- anneal_strategy: cos
- cycle_momentum: true
- base_momentum: 0.85
- max_momentum: 0.95
- div_factor: 25
- final_div_factor: 1.0e2
- three_phase: false
- last_epoch: -1
- verbose: false
- interval: step
- monitor: val/loss
+ _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+ T_max: 256
+ eta_min: 1.0e-5
+ last_epoch: -1
+ interval: epoch
+ monitor: val/loss
datamodule:
batch_size: 32
@@ -77,26 +63,25 @@ rotary_embedding: &rotary_embedding
dim: 64
attn: &attn
- dim: 192
- num_heads: 4
+ dim: &hidden_dim 256
+ num_heads: 8
dim_head: 64
- dropout_rate: 0.05
+ dropout_rate: &dropout_rate 0.5
network:
_target_: text_recognizer.networks.conv_transformer.ConvTransformer
input_dims: [1, 56, 1024]
- hidden_dim: &hidden_dim 192
+ hidden_dim: *hidden_dim
num_classes: *num_classes
pad_index: *ignore_index
encoder:
_target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
- arch: b0
- out_channels: 1280
+ arch: b2
stochastic_dropout_rate: 0.2
bn_momentum: 0.99
bn_eps: 1.0e-3
decoder:
- depth: 4
+ depth: 6
_target_: text_recognizer.networks.transformer.layers.Decoder
self_attn:
_target_: text_recognizer.networks.transformer.attention.Attention
@@ -116,7 +101,7 @@ network:
dim_out: null
expansion_factor: 4
glu: true
- dropout_rate: 0.05
+ dropout_rate: *dropout_rate
pre_norm: true
pixel_pos_embedding:
_target_: text_recognizer.networks.transformer.embeddings.axial.AxialPositionalEmbedding