metadata

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: utterance_ID
      dtype: int64
    - name: text
      dtype: string
    - name: speaker
      dtype: string
    - name: emotion
      dtype: string
    - name: video_name
      dtype: string
  splits:
    - name: train
      num_bytes: 1198989.1453851238
      num_examples: 12529
    - name: test
      num_bytes: 104309.85461487627
      num_examples: 1090
  download_size: 614184
  dataset_size: 1303299

Dataset Card for "SemEval_traindata_emotions"

Как был получен

from datasets import load_dataset
import datasets
from torchvision.io import read_video
import json
import torch
import os
from torch.utils.data import Dataset, DataLoader
import tqdm

dataset_path = "./SemEval-2024_Task3/training_data/Subtask_2_train.json"


dataset = json.loads(open(dataset_path).read())
print(len(dataset))

all_conversations = []


for item in dataset:
    all_conversations.extend(item["conversation"])
print(len(all_conversations))

all_data = datasets.Dataset.from_list(all_conversations)
all_data = all_data.train_test_split(
    test_size=0.08,
    seed=42,
)

all_data.push_to_hub(
    "dim/SemEval_training_data_emotions",
    token=open("./hf_token").read(),
)