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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: input_ids |
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sequence: int32 |
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- name: attention_mask |
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sequence: int8 |
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- name: labels |
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sequence: int64 |
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splits: |
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- name: train |
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num_bytes: 121374360 |
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num_examples: 43410 |
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- name: validation |
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num_bytes: 15171096 |
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num_examples: 5426 |
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- name: test |
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num_bytes: 15173892 |
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num_examples: 5427 |
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download_size: 2670120 |
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dataset_size: 151719348 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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# π GoEmotions Dataset (Processed for Multi-Label Classification) |
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## π Dataset Overview |
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This dataset is a **preprocessed version of the GoEmotions dataset**, containing **multi-label emotion annotations** for text inputs. It consists of **train, validation, and test splits**. |
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## π’ Dataset Statistics |
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| Split | Samples | |
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|------------|---------| |
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| **Train** | XX,XXX | |
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| **Validation** | X,XXX | |
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| **Test** | X,XXX | |
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## π Features |
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| Feature | Type | Description | |
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|-----------------|----------------|-------------| |
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| `input_ids` | `list[int]` | Tokenized input text | |
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| `attention_mask` | `list[int]` | Attention mask for tokens | |
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| `labels` | `list[int]` | Multi-label emotion encoding | |
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## π How to Load |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("codewithdark/go-emotions-processed") |
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print(dataset["train"][0]) |
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``` |
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## ποΈββοΈ Preprocessing Steps |
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- **Tokenization:** `bert-base-uncased` |
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- **Multi-label encoding:** Binary encoding of emotions |
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- **Train/Validation/Test split:** `80/10/10` |
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## π― Labels (Emotions) |
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The dataset contains **27 emotion categories**, including: |
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- Admiration, Joy, Sadness, Anger, Optimism, Disgust, Love, etc. |
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## π οΈ Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@misc{go_emotions_dataset, |
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author = {Google AI}, |
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title = {GoEmotions Dataset}, |
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year = {2021}, |
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url = {https://huggingface.co./datasets/go_emotions} |
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} |
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``` |
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