🪐 spaCy Project: Categorization of emotions in Reddit posts (Text Classification) This project uses spaCy to train a text classifier on the GoEmotions dataset
| Feature | Description |
|---|---|
| Name | en_textcat_goemotions |
| Version | 0.0.1 |
| spaCy | >=3.1.1,<3.2.0 |
| Default Pipeline | transformer, textcat_multilabel |
| Components | transformer, textcat_multilabel |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | GoEmotions dataset |
| License | MIT |
| Author | Explosion |
The dataset that this model is trained on has known flaws described here as well as label errors resulting from annotator disagreement. Anyone using this model should be aware of these limitations of the dataset.
Label Scheme
View label scheme (28 labels for 1 components)
| Component | Labels |
|---|---|
textcat_multilabel |
admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise, neutral |
Accuracy
| Type | Score |
|---|---|
CATS_SCORE |
90.22 |
CATS_MICRO_P |
66.67 |
CATS_MICRO_R |
47.81 |
CATS_MICRO_F |
55.68 |
CATS_MACRO_P |
55.00 |
CATS_MACRO_R |
41.93 |
CATS_MACRO_F |
46.29 |
CATS_MACRO_AUC |
90.22 |
CATS_MACRO_AUC_PER_TYPE |
0.00 |
TRANSFORMER_LOSS |
83.51 |
TEXTCAT_MULTILABEL_LOSS |
4549.84 |
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