Text Classification
Transformers
Safetensors
English
roberta
goemotions
emotion-classification
multi-label-classification
roberta-large
focal-loss
threshold-optimization
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use AliceYin/goemotions-roberta-large-focal-sota with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AliceYin/goemotions-roberta-large-focal-sota with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AliceYin/goemotions-roberta-large-focal-sota")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AliceYin/goemotions-roberta-large-focal-sota") model = AutoModelForSequenceClassification.from_pretrained("AliceYin/goemotions-roberta-large-focal-sota") - Notebooks
- Google Colab
- Kaggle
| { | |
| "coordinate": { | |
| "admiration": 0.49000000953674316, | |
| "amusement": 0.4699999988079071, | |
| "anger": 0.44999998807907104, | |
| "annoyance": 0.3700000047683716, | |
| "approval": 0.38999998569488525, | |
| "caring": 0.33000001311302185, | |
| "confusion": 0.4099999964237213, | |
| "curiosity": 0.4099999964237213, | |
| "desire": 0.4099999964237213, | |
| "disappointment": 0.3700000047683716, | |
| "disapproval": 0.38999998569488525, | |
| "disgust": 0.4099999964237213, | |
| "embarrassment": 0.3499999940395355, | |
| "excitement": 0.44999998807907104, | |
| "fear": 0.44999998807907104, | |
| "gratitude": 0.4699999988079071, | |
| "grief": 0.28999999165534973, | |
| "joy": 0.4099999964237213, | |
| "love": 0.49000000953674316, | |
| "nervousness": 0.3700000047683716, | |
| "neutral": 0.1899999976158142, | |
| "optimism": 0.4099999964237213, | |
| "pride": 0.3100000023841858, | |
| "realization": 0.4699999988079071, | |
| "relief": 0.33000001311302185, | |
| "remorse": 0.33000001311302185, | |
| "sadness": 0.38999998569488525, | |
| "surprise": 0.3700000047683716 | |
| }, | |
| "fixed_0_5": { | |
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| "annoyance": 0.5, | |
| "approval": 0.5, | |
| "caring": 0.5, | |
| "confusion": 0.5, | |
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| "desire": 0.5, | |
| "disappointment": 0.5, | |
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| "fear": 0.5, | |
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| "grief": 0.5, | |
| "joy": 0.5, | |
| "love": 0.5, | |
| "nervousness": 0.5, | |
| "neutral": 0.5, | |
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| "pride": 0.5, | |
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| "relief": 0.5, | |
| "remorse": 0.5, | |
| "sadness": 0.5, | |
| "surprise": 0.5 | |
| }, | |
| "global": { | |
| "per_label": { | |
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| "surprise": 0.3700000047683716 | |
| }, | |
| "value": 0.37 | |
| }, | |
| "per_label": { | |
| "admiration": 0.49000000953674316, | |
| "amusement": 0.4699999988079071, | |
| "anger": 0.44999998807907104, | |
| "annoyance": 0.3700000047683716, | |
| "approval": 0.3700000047683716, | |
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| "confusion": 0.4099999964237213, | |
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| "desire": 0.4099999964237213, | |
| "disappointment": 0.3700000047683716, | |
| "disapproval": 0.38999998569488525, | |
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| "excitement": 0.44999998807907104, | |
| "fear": 0.44999998807907104, | |
| "gratitude": 0.4699999988079071, | |
| "grief": 0.28999999165534973, | |
| "joy": 0.4099999964237213, | |
| "love": 0.49000000953674316, | |
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| "neutral": 0.3700000047683716, | |
| "optimism": 0.4099999964237213, | |
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| "realization": 0.4699999988079071, | |
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| "sadness": 0.38999998569488525, | |
| "surprise": 0.3700000047683716 | |
| }, | |
| "selected": "coordinate", | |
| "selection_metric": "macro_f1" | |
| } | |