Slim config.yaml to inference-only TimeSeriesModel architecture
Browse files- config.yaml +0 -64
config.yaml
CHANGED
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@@ -1,67 +1,3 @@
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train_data_path: ./forge_synth_data
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model_path: ./forge_checkpoints
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model_name: Forge_1M
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continue_training: false
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checkpoint_path: null
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seed: 2025
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wandb: false
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wandb_project_name: Forge
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wandb_plots: false
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batch_size: 400
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num_training_iterations: 150000
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validation_batch_size: 64
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num_validation_batches: 1
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num_workers: 16
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prefetch_arrow_batches: true
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dataloader_prefetch_factor: 4
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gradient_accumulation_enabled: false
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accumulation_steps: 1
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log_interval: 1024
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save_every: 25000
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memory_debug_interval: 0
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memory_debug_tracemalloc: false
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memory_debug_growth_mb: 40
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memory_debug_include_children: true
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generator_proportions:
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forecast_pfn: 1.0
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gp: 1.0
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kernel: 1.0
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sawtooth: 1.0
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sinewave: 1.0
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step: 1.0
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anomaly: 1.0
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spike: 1.0
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cauker_univariate: 1.0
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ou_process: 3.0
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augmented_per_sample_2048: 2.0
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augmented_temp_batch_2048: 2.0
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lr_scheduler: cosine
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peak_lr: 0.0005
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min_lr_ratio: 0.01
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warmup_ratio: 0.003
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stable_ratio: 0.9
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decay_type: cosine
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num_cycles: 0.5
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num_restart_cycles: 4
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weight_decay: 0.01
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beta1: 0.9
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beta2: 0.98
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optimizer_eps: 1e-6
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gradient_clip_val: 100.0
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scaler: custom_robust
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gift_eval:
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evaluate_on_gift_eval: false
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max_context_length: 3072
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create_plots: false
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max_plots: 5
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dataset_storage_path: null
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data_augmentation:
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nan_augmentation: true
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scaler_augmentation: false
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length_shortening: true
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nan_stats_path: ../tempopfn/src/data/nan_stats.json
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augmentation_probabilities:
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scaler_augmentation: 0.5
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TimeSeriesModel:
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embed_size: 128
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num_encoder_layers: 3
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TimeSeriesModel:
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embed_size: 128
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num_encoder_layers: 3
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