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sig-autoencoder-fourier-5-simclr-mse

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sig-autoencoder-fourier-5-simclr-mse
File size: 2,331 Bytes 
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architecture:
  latent_dim: 256
  mlp:
    decoder:
      activation: relu
      batch_norm: true
      dropout: 0.2
      hidden_dims:
      - 256
      - 384
      - 512
    encoder:
      activation: relu
      batch_norm: true
      dropout: 0.2
      hidden_dims:
      - 512
      - 384
      - 256
    token_pooling: mean
  transformer:
    decoder:
      activation: relu
      d_model: 512
      dim_feedforward: 2048
      dropout: 0.1
      num_heads: 8
      num_layers: 6
    encoder:
      activation: relu
      d_model: 512
      dim_feedforward: 2048
      dropout: 0.1
      num_heads: 8
      num_layers: 6
      pooling: mean
      positional_encoding: learned
  type: transformer
dataloader:
  num_workers: 0
  pin_memory: true
dataset:
  hf_dataset: maximuspowers/muat-fourier-5
  input_mode: signature
  max_dimensions:
    max_hidden_layers: 6
    max_neurons_per_layer: 8
    max_sequence_length: 5
  neuron_profile:
    methods:
    - fourier
  random_seed: 42
  test_split: 0.1
  train_split: 0.8
  val_split: 0.1
device:
  type: auto
evaluation:
  metrics:
  - mse
  - mae
  - rmse
  - cosine_similarity
  - relative_error
  - r2_score
  per_layer_metrics: false
hub:
  enabled: true
  private: false
  push_logs: true
  push_metrics: true
  push_model: true
  repo_id: maximuspowers/sig-autoencoder-fourier-5-simclr-mse
  token: <REDACTED>
logging:
  checkpoint:
    enabled: true
    mode: min
    monitor: val_loss
    save_best_only: true
  tensorboard:
    auto_launch: true
    enabled: true
    log_interval: 10
    port: 6006
  verbose: true
loss:
  augmentation_type: noise
  contrast_type: simclr
  dropout_prob: 0.1
  gamma: 0.4
  noise_std: 0.01
  projection_head:
    hidden_dim: 256
    input_dim: 256
    output_dim: 128
  reconstruction_type: mse
  temperature: 0.1
  type: contrastive
run_dir: /Users/max/Desktop/muat/model_zoo/runs/train-encoder-decoder_config_2025-12-11_16-05-33
run_log_cleanup: false
tokenization:
  chunk_size: 64
  include_metadata: true
  max_tokens: 512
training:
  batch_size: 8
  early_stopping:
    enabled: true
    mode: min
    monitor: val_loss
    patience: 5
  epochs: 100
  learning_rate: 0.0001
  lr_scheduler:
    enabled: true
    factor: 0.5
    min_lr: 1.0e-06
    patience: 3
    type: reduce_on_plateau
  optimizer: adam
  weight_decay: 0.0001