1 files changed, 0 insertions, 132 deletions
diff --git a/training/conf/experiment/conv_transformer_paragraphs.yaml b/training/conf/experiment/conv_transformer_paragraphs.yaml
deleted file mode 100644
index 9df2ea9..0000000
--- a/training/conf/experiment/conv_transformer_paragraphs.yaml
+++ /dev/null
@@ -1,132 +0,0 @@
-# @package _global_
-
-defaults:
-  - override /criterion: cross_entropy
-  - override /callbacks: htr
-  - override /datamodule: iam_extended_paragraphs
-  - override /network: null
-  - override /model: lit_transformer
-  - override /lr_scheduler: null
-  - override /optimizer: null
-
-tags: [paragraphs]
-epochs: &epochs 256
-ignore_index: &ignore_index 3
-# max_output_len: &max_output_len 682
-# summary: [[1, 1, 576, 640], [1, 682]]
-
-logger:
-  wandb:
-    tags: ${tags}
-
-criterion:
-  ignore_index: *ignore_index
-  # label_smoothing: 0.05
-
-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: 3.0e-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: 4
-  train_fraction: 0.95
-
-network:
-  _target_: text_recognizer.network.ConvTransformer
-  encoder:
-    _target_: text_recognizer.network.image_encoder.ImageEncoder
-    encoder:
-      _target_: text_recognizer.network.convnext.ConvNext
-      dim: 16
-      dim_mults: [1, 2, 4, 8, 32]
-      depths: [2, 3, 3, 3, 6]
-      downsampling_factors: [[2, 2], [2, 2], [2, 2], [2, 1], [2, 1]]
-      attn:
-        _target_: text_recognizer.network.convnext.TransformerBlock
-        attn:
-          _target_: text_recognizer.network.convnext.Attention
-          dim: &dim 512
-          heads: 4
-          dim_head: 64
-          scale: 8
-        ff:
-          _target_: text_recognizer.network.convnext.FeedForward
-          dim: *dim
-          mult: 2
-    pixel_embedding:
-      _target_: "text_recognizer.network.transformer.embeddings.axial.\
-        AxialPositionalEmbeddingImage"
-      dim: *dim
-      axial_shape: [18, 80]
-  decoder:
-    _target_: text_recognizer.network.text_decoder.TextDecoder
-    dim: *dim
-    num_classes: 58
-    pad_index: *ignore_index
-    decoder:
-      _target_: text_recognizer.network.transformer.Decoder
-      dim: *dim
-      depth: 6
-      block:
-        _target_: "text_recognizer.network.transformer.decoder_block.\
-          DecoderBlock"
-        self_attn:
-          _target_: text_recognizer.network.transformer.Attention
-          dim: *dim
-          num_heads: 8
-          dim_head: &dim_head 64
-          dropout_rate: &dropout_rate 0.2
-          causal: true
-        cross_attn:
-          _target_: text_recognizer.network.transformer.Attention
-          dim: *dim
-          num_heads: 8
-          dim_head: *dim_head
-          dropout_rate: *dropout_rate
-          causal: false
-        norm:
-          _target_: text_recognizer.network.transformer.RMSNorm
-          dim: *dim
-        ff:
-          _target_: text_recognizer.network.transformer.FeedForward
-          dim: *dim
-          dim_out: null
-          expansion_factor: 2
-          glu: true
-          dropout_rate: *dropout_rate
-      rotary_embedding:
-        _target_: text_recognizer.network.transformer.RotaryEmbedding
-        dim: *dim_head
-
-trainer:
-  gradient_clip_val: 1.0
-  max_epochs: *epochs
-  accumulate_grad_batches: 2
-  limit_train_batches: 1.0
-  limit_val_batches: 1.0
-  limit_test_batches: 1.0