results/episode_task_suite/neural_mlp/object_relevance/metrics.json

{
  "micro_f1": 0.1679279279279279,
  "macro_f1": 0.048883162556964774,
  "exact_match": 0.014367816091954023,
  "precision": 0.16431593794076163,
  "recall": 0.17170228445099484,
  "task": "object_relevance",
  "input": "all non-caption modalities -> current relevant object set",
  "split": "chronological",
  "num_windows": 1161,
  "num_train_windows": 813,
  "num_test_windows": 348,
  "num_objects": 34,
  "feature_dim": 7650,
  "model": "neural_mlp",
  "head": "z-score -> MLP sigmoid multilabel",
  "neural_epochs": 80,
  "neural_hidden_dim": 128,
  "neural_batch_size": 128,
  "neural_learning_rate": 0.001,
  "neural_weight_decay": 0.0001,
  "neural_dropout": 0.1,
  "neural_device": "cpu",
  "train_final_loss": 0.003651880362182214,
  "task_display_name": "Object Relevance Prediction"
}