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--- |
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tags: |
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- spacy |
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- text-classification |
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language: |
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- en |
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license: mit |
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model-index: |
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- name: en_textcat_goemotions |
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results: [] |
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--- |
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# 🪐 spaCy Project: Categorization of emotions in Reddit posts (Text Classification) This project uses spaCy to train a text classifier on the [GoEmotions dataset](https://github.com/google-research/google-research/tree/master/goemotions) |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_textcat_goemotions` | |
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| **Version** | `0.0.1` | |
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| **spaCy** | `>=3.1.1,<3.2.0` | |
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| **Default Pipeline** | `transformer`, `textcat_multilabel` | |
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| **Components** | `transformer`, `textcat_multilabel` | |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
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| **Sources** | [GoEmotions dataset](https://github.com/google-research/google-research/tree/master/goemotions) | |
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| **License** | `MIT` | |
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| **Author** | [Explosion](explosion.ai) | |
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> The dataset that this model is trained on has known flaws described [here](https://github.com/google-research/google-research/tree/master/goemotions#disclaimer) as well as label errors resulting from [annotator disagreement](https://www.youtube.com/watch?v=khZ5-AN-n2Y). Anyone using this model should be aware of these limitations of the dataset. |
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### Label Scheme |
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<details> |
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<summary>View label scheme (28 labels for 1 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`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` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `CATS_SCORE` | 90.22 | |
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| `CATS_MICRO_P` | 66.67 | |
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| `CATS_MICRO_R` | 47.81 | |
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| `CATS_MICRO_F` | 55.68 | |
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| `CATS_MACRO_P` | 55.00 | |
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| `CATS_MACRO_R` | 41.93 | |
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| `CATS_MACRO_F` | 46.29 | |
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| `CATS_MACRO_AUC` | 90.22 | |
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| `CATS_MACRO_AUC_PER_TYPE` | 0.00 | |
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| `TRANSFORMER_LOSS` | 83.51 | |
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| `TEXTCAT_MULTILABEL_LOSS` | 4549.84 | |
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