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EVAL.IR_evaluation

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metadata
dataset_info:
  features:
    - name: question
      dtype: string
    - name: answer
      dtype: string
    - name: url
      dtype: string
    - name: group
      dtype: string
    - name: doc_id
      dtype: string
    - name: evaluation
      list:
        - name: content
          dtype: string
        - name: doc_id
          dtype: string
        - name: score
          dtype: float64
    - name: metadata
      dtype: string
  splits:
    - name: TEST.basic_test_tdt_dataset
      num_bytes: 189180
      num_examples: 20
    - name: INDEX.medium_index_TDT
      num_bytes: 4968179
      num_examples: 144
    - name: INDEX.medium_index_TDT.hyde_vector
      num_bytes: 778218
      num_examples: 144
    - name: INDEX.medium_index_TDT.proposition.hybrid
      num_bytes: 2461761
      num_examples: 144
    - name: INDEX.medium_index_TDT.proposition.sentence.hybrid
      num_bytes: 375307
      num_examples: 144
    - name: INDEX.medium_index_TDT.fulltext.clean.proposition.sentence.hybrid
      num_bytes: 5984807
      num_examples: 144
    - name: INDEX.medium_index_TDT.fulltext.clean.8.proposition.sentence.hybrid
      num_bytes: 2139530
      num_examples: 144
    - name: INDEX.medium_index_TDT.fulltext.clean.2.proposition.sentence.hybrid
      num_bytes: 1063217
      num_examples: 144
    - name: TEST.basic_raptor_TDT
      num_bytes: 345012.43055555556
      num_examples: 10
  download_size: 2280352
  dataset_size: 18305211.430555556
configs:
  - config_name: default
    data_files:
      - split: TEST.basic_test_tdt_dataset
        path: data/TEST.basic_test_tdt_dataset-*
      - split: INDEX.medium_index_TDT
        path: data/INDEX.medium_index_TDT-*
      - split: INDEX.medium_index_TDT.hyde_vector
        path: data/INDEX.medium_index_TDT.hyde_vector-*
      - split: INDEX.medium_index_TDT.proposition.hybrid
        path: data/INDEX.medium_index_TDT.proposition.hybrid-*
      - split: INDEX.medium_index_TDT.proposition.sentence.hybrid
        path: data/INDEX.medium_index_TDT.proposition.sentence.hybrid-*
      - split: INDEX.medium_index_TDT.fulltext.clean.proposition.sentence.hybrid
        path: >-
          data/INDEX.medium_index_TDT.fulltext.clean.proposition.sentence.hybrid-*
      - split: INDEX.medium_index_TDT.fulltext.clean.8.proposition.sentence.hybrid
        path: >-
          data/INDEX.medium_index_TDT.fulltext.clean.8.proposition.sentence.hybrid-*
      - split: INDEX.medium_index_TDT.fulltext.clean.2.proposition.sentence.hybrid
        path: >-
          data/INDEX.medium_index_TDT.fulltext.clean.2.proposition.sentence.hybrid-*
      - split: TEST.basic_raptor_TDT
        path: data/TEST.basic_raptor_TDT-*

Evaluation results on IR

Evaluation results

Rules for creating split

There are some rules:

  1. The name of split should be based on a split from "BroDeadlines/TEST.edu_tdt_data"
  2. After the second "." can be something about the run results

Results

TEST.basic_test_tdt_dataset

{
  "split": "TEST.basic_test_tdt_dataset",
  "algo": "HyDE",
  "size": "20",
  "precision": 0.625,
  "recall": 0.5,
  "map": 0.354
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_data',
  'data_split': 'INDEX.medium_index_TDT',
  'vec_index': 'vec-index.medium_index_tdt',
  'text_index': 'text-index.medium_index_tdt',
  'algo': 'HyDE-Hybrid',
  'search_algo': 'vector search',
  'size': 142, 
  'precision': 0.2485207100591716,
  'recall': 0.29577464788732394,
  'map_score': 0.13399564050972498
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT.hyde_vector',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_proposition_data',
  'data_split': 'train',
  'vec_index': 'vec-index.medium_index_tdt',
  'algo': ['HyDE', 'proposition', 'vector search'],
  'size': 143,
  'precision': 0.2823529411764706,
  'recall': 0.16783216783216784,
  'map_score': 0.09790209790209793
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT.proposition.sentence.hybrid',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_proposition_data',
  'data_split': 'train',
  'vec_index': 'vec-sentence-propositon_medium_edu_tdt',
  'text_index': 'text-sentence-propositon_medium_edu_tdt',
  'algo': ['HyDE', 'hybrid search', 'proposition', 'sentence-encoding', 'parent document retrieval'],
  'size': 144,
  'hybrid_weigths': [0.4, 0.6],
  'precision': 0.6650485436893204,
  'recall': 0.9513888888888888,
  'map_score': 0.16559069113756608
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT.fulltext.clean.proposition.sentence.hybrid',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_proposition_data',
  'data_split': 'INDEX.medium_index_TDT_clean',
  'vec_index': 'vec-sentence-index.medium_index_tdt_clean',
  'text_index': 'text-sentence-index.medium_index_tdt_clean',
  'algo': ['HyDE', 'hybrid search', 'proposition', 'full-text-encoding']
  'total_k': 20,
  'relevant': 0.7569444444444444,
  'precision': 0.4052044609665427,
  'recall': 0.7569444444444444,
  'map_score': 0.19089647598822646,
  'relevant_retrieved': 109,
  'num_retrieved': 269
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT.fulltext.clean.8.proposition.sentence.hybrid',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_proposition_data',
  'data_split': 'INDEX.medium_index_TDT_clean',
  'vec_index': 'vec-sentence-index.medium_index_tdt_clean',
  'text_index': 'text-sentence-index.medium_index_tdt_clean',
  'algo': ['HyDE', 'hybrid search', 'proposition', 'full-text-encoding']
  'total_k': 8,
  'relevant': 0.5902777777777778,
  'precision': 0.425,
  'recall': 0.5902777777777778,
  'map_score': 0.3272982804232805,
  'relevant_retrieved': 85,
  'num_retrieved': 200
}

INDEX.medium_index_TDT

{
  'split': 'INDEX.medium_index_TDT.fulltext.clean.2.proposition.sentence.hybrid',
  'data_repo': 'https://huggingface.co/datasets/BroDeadlines/TEST.edu_tdt_proposition_data',
  'data_split': 'INDEX.medium_index_TDT_clean',
  'vec_index': 'vec-sentence-index.medium_index_tdt_clean',
  'text_index': 'text-sentence-index.medium_index_tdt_clean',
  'algo': ['HyDE', 'hybrid search', 'proposition', 'full-text-encoding']
  'total_k': 4,
  'relevant': 0.4652777777777778,
  'precision': 0.46206896551724136,
  'recall': 0.4652777777777778,
  'map_score': 0.2957175925925926,
  'relevant_retrieved': 67,
  'num_retrieved': 145
}