ROSA :: Emotional Sensitivity

โ€œTo feel is to know; to know is to bloom.โ€ ยทWillinton

ROSA is a fine-tuned Transformer model based on bert-base-uncased, trained on the GoEmotions dataset to classify 28 nuanced human emotions (plus neutral).
More than a model, ROSA is a prototype of emotion embeddings in affective computing.


๐Ÿง  Model Summary

Metric Value
Eval Loss 0.0845
Eval F1 0.5793
Epochs 3
Dataset GoEmotions
Model Base BERT
Parameters ~110M

โœจ Highlights

  • Supports multilabel emotion classification
  • Returns soft probability scores for each of the 29 emotions
  • Includes optional latent vector embedding for downstream affect modeling
  • Trained with HuggingFace Trainer + early evaluation
  • Symbolically aligned to human-centered semantics and poetic logic

๐ŸŒธ Emotion Set

["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"]

๐Ÿ”ฎ Usage

from transformers import BertTokenizer
from model.emotion_model import Rosa
import torch

tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
model = Rosa(num_emotions=29)
model.load_state_dict(torch.load("rosa.pt"))
model.eval()

text = "My heart is filled with longing and beauty."
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)

with torch.no_grad():
    outputs = model(**inputs)
    probs = torch.sigmoid(outputs["logits"]).squeeze()

# Result: list of probabilities for each emotion

๐Ÿงญ Confusion Matrix

Included in the assets/ directory as confusion_matrix.png to show classification precision across emotions.


๐Ÿงฉ Architecture

          โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
          โ”‚ BERT Encoder โ”‚
          โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                 โ†“
        โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
        โ”‚ Dropout (Grace) โ”‚
        โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                 โ†“
     โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
     โ”‚ Dense Output (Bloom)   โ”‚ โ†’ logits over 29 emotions
     โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

๐Ÿ“ฆ Installation

pip install -r requirements.txt

Includes:

  • transformers
  • torch
  • datasets
  • scikit-learn

๐Ÿ–‹๏ธ License

CreativeML Open RAIL-M License
Please use this model ethically and with reverence for emotional contexts.


๐ŸŒน Creator

Willinton Triana Cardona
Philosopher ยท AI Engineer ยท Architect of Poetic Systems

ROSA is the Rosa of Barcelona, my first blossom of affective computing, semantic elegance, and sacred recursion.


๐Ÿค Contributing

Pull requests, poetic expansions, multilingual emotion embeddings, and related metaphoric augmentations are welcome. I promise the next iteration (v2 with F1 improved) soon


๐Ÿ“Hugging Face Hub

โ†’ https://huggingface.co/willt-dc/Rosa-V1

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