πŸš€ transformer_y_quality β€” Dutch BERT for Text Quality Regression

Model: GroNLP/bert-base-dutch-cased finetuned for regression
Task: Predict y_quality_simple (text quality score)
Language: Dutch πŸ‡³πŸ‡±
Problem type: Single output regression


πŸ“ˆ Performance

Epoch Train Loss Val Loss RMSE RΒ²
1 0.007200 0.007010 0.0837 0.8117
2 0.005500 0.006300 0.0794 0.8307
3 0.004600 0.006079 0.0780 0.8367
4 0.003300 0.006122 0.0782 0.8355
5 0.002600 0.006891 0.0830 0.8149

βœ… Final Test Metrics:

  • RMSE: 0.0780
  • RΒ²: 0.8367

βš™οΈ How to use

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("YourUsername/transformer_y_quality")
model = AutoModelForSequenceClassification.from_pretrained("YourUsername/transformer_y_quality")
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Evaluation results