---
license: mit
dataset_info:
  config_name: google_translator
  features:
  - name: lt_text
    dtype: string
  - name: text
    dtype: string
  - name: labels
    sequence:
      class_label:
        names:
          '0': admiration
          '1': amusement
          '2': anger
          '3': annoyance
          '4': approval
          '5': caring
          '6': confusion
          '7': curiosity
          '8': desire
          '9': disappointment
          '10': disapproval
          '11': disgust
          '12': embarrassment
          '13': excitement
          '14': fear
          '15': gratitude
          '16': grief
          '17': joy
          '18': love
          '19': nervousness
          '20': optimism
          '21': pride
          '22': realization
          '23': relief
          '24': remorse
          '25': sadness
          '26': surprise
          '27': neutral
  - name: labels_ekman
    sequence:
      class_label:
        names:
          '0': anger
          '1': disgust
          '2': fear
          '3': joy
          '4': sadness
          '5': surprise
          '6': neutral
  - name: id
    dtype: string
  splits:
  - name: train
    num_bytes: 7095238
    num_examples: 43410
  - name: validation
    num_bytes: 885284
    num_examples: 5426
  - name: test
    num_bytes: 882333
    num_examples: 5427
  download_size: 6057071
  dataset_size: 8862855
configs:
- config_name: google_translator
  data_files:
  - split: train
    path: google_translator/train-*
  - split: validation
    path: google_translator/validation-*
  - split: test
    path: google_translator/test-*
task_categories:
- text-classification
language:
- en
- lt
---
Original dataset: [GoEmotions dataset](https://huggingface.co/datasets/google-research-datasets/go_emotions)

The dataset was machine translated to Lithuanian using free Google Translate API.

Tool used for translation: [deep-translator](https://pypi.org/project/deep-translator/)

Translation script:
```python
from datasets import load_dataset
from deep_translator import GoogleTranslator
from deep_translator.exceptions import TranslationNotFound

original_dataset = load_dataset("go_emotions", name="simplified")
translator = GoogleTranslator(source="en", target="lt")

def translate_batch(batch):
    original_text = batch["text"]

    while True:
        try:
            translated_batch = translator.translate_batch(original_text)
            break
        except TranslationNotFound:
            # Translation can fail due to API limits, so we retry until it works
            print(f"Translation failed. Retrying...")
    
    # We fix untranslated entries (None values) by replacing them with the original text
    for i in range(len(translated_batch)):
        if not translated_batch[i]:
            translated_batch[i] = original_text[i]
            print(f"Replaced {original_text[i]} vs {translated_batch[i]}")
            
    batch["lt_text"] = translated_batch
    
    return batch

translated_dataset = original_dataset.map(
    translate_batch, batched=True, batch_size=500
)
```

Column `labels` contains multi-label emotion annotations with 28 emotion labels as per GoEmotion dataset:
```yaml
0: admiration
1: amusement
2: anger
3: annoyance
4: approval
5: caring
6: confusion
7: curiosity
8: desire
9: disappointment
10: disapproval
11: disgust
12: embarrassment
13: excitement
14: fear
15: gratitude
16: grief
17: joy
18: love
19: nervousness
20: optimism
21: pride
22: realization
23: relief
24: remorse
25: sadness
26: surprise
27: neutral
```

Column `labels_ekman` contains multi-label emotion annotations with 7 base emotions as per Dr. Ekman theory:
```yaml
0: anger
1: disgust
2: fear
3: joy
4: sadness
5: surprise
6: neutral
```

Label mapping from 28 emotions from GoEmotion to 7 base emotions as per Dr. Ekman theory:
|GoEmotion|Ekman|
|---|---|
| admiration | joy|
| amusement | joy|
| anger | anger|
| annoyance | anger|
| approval | joy|
| caring | joy|
| confusion | surprise|
| curiosity | surprise|
| desire | joy|
| disappointment | sadness|
| disapproval | anger|
| disgust | disgust|
| embarrassment | sadness|
| excitement | joy|
| fear | fear|
| gratitude | joy|
| grief | sadness|
| joy | joy|
| love | joy|
| nervousness | fear|
| optimism | joy|
| pride | joy|
| realization | surprise|
| relief | joy|
| remorse | sadness|
| sadness | sadness|
| surprise | surprise|
| neutral | neutral|