README.md

metadata

language: en
size_categories: 10K<n<100K
task_categories:
  - text-classification
task_ids:
  - multi-class-classification
  - topic-classification
tags:
  - long context
dataset_info:
  - config_name: abstract
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': Human Necessities
              '1': Performing Operations; Transporting
              '2': Chemistry; Metallurgy
              '3': Textiles; Paper
              '4': Fixed Constructions
              '5': Mechanical Engineering; Lightning; Heating; Weapons; Blasting
              '6': Physics
              '7': Electricity
              '8': General tagging of new or cross-sectional technology
    splits:
      - name: train
        num_bytes: 17225101
        num_examples: 25000
      - name: validation
        num_bytes: 3472854
        num_examples: 5000
      - name: test
        num_bytes: 3456733
        num_examples: 5000
    download_size: 12067953
    dataset_size: 24154688
  - config_name: patent
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': Human Necessities
              '1': Performing Operations; Transporting
              '2': Chemistry; Metallurgy
              '3': Textiles; Paper
              '4': Fixed Constructions
              '5': Mechanical Engineering; Lightning; Heating; Weapons; Blasting
              '6': Physics
              '7': Electricity
              '8': General tagging of new or cross-sectional technology
    splits:
      - name: train
        num_bytes: 466788625
        num_examples: 25000
      - name: validation
        num_bytes: 95315107
        num_examples: 5000
      - name: test
        num_bytes: 93844869
        num_examples: 5000
    download_size: 272966251
    dataset_size: 655948601
configs:
  - config_name: abstract
    data_files:
      - split: train
        path: abstract/train-*
      - split: validation
        path: abstract/validation-*
      - split: test
        path: abstract/test-*
  - config_name: patent
    data_files:
      - split: train
        path: patent/train-*
      - split: validation
        path: patent/validation-*
      - split: test
        path: patent/test-*
    default: true

Patent Classification: a classification of Patents and abstracts (9 classes).

This dataset is intended for long context classification (non abstract documents are longer that 512 tokens).
Data are sampled from "BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization." by Eva Sharma, Chen Li and Lu Wang

• See: https://aclanthology.org/P19-1212.pdf
• See: https://evasharma.github.io/bigpatent/

It contains 9 unbalanced classes, 35k Patents and abstracts divided into 3 splits: train (25k), val (5k) and test (5k).

Note that documents are uncased and space separated (by authors)

Compatible with run_glue.py script:

export MODEL_NAME=roberta-base
export MAX_SEQ_LENGTH=512

python run_glue.py \
  --model_name_or_path $MODEL_NAME \
  --dataset_name ccdv/patent-classification  \
  --do_train \
  --do_eval \
  --max_seq_length $MAX_SEQ_LENGTH \
  --per_device_train_batch_size 8 \
  --gradient_accumulation_steps 4 \
  --learning_rate 2e-5 \
  --num_train_epochs 1 \
  --max_eval_samples 500 \
  --output_dir tmp/patent