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distilbert-base-uncased, fine-tuneddistilbert-base-uncasedjingjietan/essays-big5 dataset1from transformers import AutoTokenizer, AutoModelForSequenceClassification
2
3model = AutoModelForSequenceClassification.from_pretrained("vladinc/bigfive-regression-model")
4tokenizer = AutoTokenizer.from_pretrained("vladinc/bigfive-regression-model")
5
6text = "I enjoy reflecting on abstract concepts and trying new things."
7inputs = tokenizer(text, return_tensors="pt")
8outputs = model(**inputs)
9
10print(outputs.logits) # 5 float scores between 0.0 and 1.0
11
12Training Details
13Training Data
14Dataset: jingjietan/essays-big5
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16Format: Essay text + 5 numeric labels for personality traits
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18Training Procedure
19Epochs: 3
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21Batch size: 8
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23Learning rate: 2e-5
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25Loss Function: Mean Squared Error
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27Metric for Best Model: MSE on Openness
28
29Evaluation
30Metrics
31Trait Validation MSE
32Openness 0.324
33Conscientiousness 0.537
34Extraversion 0.680
35Agreeableness 0.441
36Neuroticism 0.564
37
38Citation
39If you use this model, please cite it:
40
41BibTeX:
42
43bibtex
44Copy
45Edit
46@misc{vladinc2025bigfive,
47 title={Big Five Personality Regression Model},
48 author={vladinc},
49 year={2025},
50 howpublished={\\url{https://huggingface.co/vladinc/bigfive-regression-model}}
51}
52Contact
53If you have questions or suggestions, feel free to reach out via the Hugging Face profile.