HH FA brain.Event:2R. ,tensorboard.summary.writer.event_file_writerZ{]`/# FA*  hp_metric5 FA* _hparams_/experimentJ hparams  " hidden_dim " transformer_dim " transformer_dim_scale " initial_embedding_dim " position_embedding_dim " num_embedding_layers " num_encoder_layers " num_branch_embedding_layers " num_branch_encoder_layers " num_jet_embedding_layers " num_jet_encoder_layers " num_detector_layers " num_regression_layers " num_classification_layers " split_symmetric_attention " num_attention_heads " transformer_activation " skip_connections "& "initial_embedding_skip_connections " linear_block_type " transformer_type " linear_activation " normalization " masking " linear_prelu_activation " use_pairwise_interactions " num_pairwise_features " pairwise_embedding_dim " pairwise_input_source " use_moe " num_experts " num_experts_per_tok " moe_loss_scale " event_info_file " training_file " validation_file " testing_file " normalize_features " limit_to_num_jets " balance_particles " balance_jets " balance_classifications " partial_events " dataset_limit " dataset_randomization " train_validation_split " limit_val_batches " batch_size " num_dataloader_workers " mask_sequence_vectors " combine_pair_loss " optimizer " learning_rate " focal_gamma " combinatorial_scale " learning_rate_warmup_epochs " learning_rate_cycles " assignment_loss_scale " detection_loss_scale " kl_loss_scale " regression_loss_scale " classification_loss_scale " use_mass_classification " balance_losses " l2_penalty " gradient_clip " dropout " epochs " num_gpu " verbose_output " usable_gpus " trial_time " trial_output_dir *  hp_metricIb : FA*  _hparams_/session_start_infoJ  hparams ( num_branch_embedding_layers @ " initial_embedding_dim `@ ! learning_rate_cycles ?  limit_val_batches ?  pairwise_input_source num_experts_per_tok @ # num_jet_encoder_layers @ ( learning_rate_warmup_epochs ?  masking Filling  balance_losses ? " num_pairwise_features @ H training_file75/data/spatop/tpm70_wpm30_FB350_training/all_merged.h5 & num_classification_layers @ " dataset_randomization  & use_pairwise_interactions   balance_jets   hidden_dim `@  transformer_dim `@  gradient_clip $@ $ balance_classifications   skip_connections ?  balance_particles   learning_rate ͎3?  focal_gamma  % num_jet_embedding_layers  # pairwise_embedding_dim  @ & num_branch_encoder_layers @ # num_dataloader_workers  @ ! detection_loss_scale ? & split_symmetric_attention ? " num_regression_layers @  use_moe   kl_loss_scale   combine_pair_lossmin num_attention_heads  @  limit_to_num_jets  num_detector_layers @  normalization  LayerNorm " regression_loss_scale  combinatorial_scale  J event_info_file75/data/spatop/event_files/v11/tt_hadronic_v7_full.yaml  testing_file  linear_activationgelu ! num_embedding_layers ,@ $ use_mass_classification  " assignment_loss_scale ?  transformer_typeGated  linear_block_typeGRU  dataset_limit ? / "initial_embedding_skip_connections ?  normalize_features ?  num_experts  @  partial_events ? " mask_sequence_vectors ?  verbose_output   usable_gpus $ linear_prelu_activation ? & classification_loss_scale  # train_validation_split ffffff?  num_encoder_layers @  num_gpu ?  moe_loss_scale {Gz?  l2_penalty -C6*?  batch_size @  epochs Y@ # trial_output_dir ./test_output  validation_file  trial_time  optimizerAdamW  dropout Y? " transformer_dim_scale @ # position_embedding_dim `@ transformer_activationgeluc<ȷR FA*1 / _hparams_/session_end_infoJ  hparams"e