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metadata
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype: string
  splits:
    - name: train
      num_bytes: 105750984.56504539
      num_examples: 152946
    - name: test
      num_bytes: 22660826.48866134
      num_examples: 32774
    - name: val
      num_bytes: 22661517.91560003
      num_examples: 32775
  download_size: 65442094
  dataset_size: 151073328.96930677
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: val
        path: data/val-*

Dataset Card for "vibhorag101/suicide_prediction_dataset_phr"

  • The dataset is sourced from Reddit and is available on Kaggle.
  • The dataset contains text with binary labels for suicide or non-suicide.
  • The dataset was cleaned minimally, as BERT depends on contextually sensitive information, which can worsely effect its performance.
    • Removed numbers
    • Removed URLs, Emojis, and accented characters.
    • Remove any extra white spaces and any extra spaces after a single space.
    • Removed any consecutive characters repeated more than 3 times.
    • The rows with more than 512 BERT Tokens were removed, as they exceeded BERT's max token limit.
  • The cleaned dataset can be found here
  • The evaluation set had ~33k samples, while the training set had ~153k samples, i.e., a 70:15:15 (train:test:val) split.