xlm-roberta-base-pre-mrp-14012025-1347-42
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp
Pre-Finetuned Model: None
Training Information
Epochs: 4
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.186030
Validation Accuracy: 0.938416
Validation F1: 0.551309
Classification Report
{'0': {'precision': 0.943362311262174, 'recall': 0.9941107590577215, 'f1-score': 0.9680719052889292, 'support': 29036.0}, '1': {'precision': 0.46394984326018807, 'recall': 0.0786815523657629, 'f1-score': 0.13454545454545455, 'support': 1881.0}, 'accuracy': 0.938415758320665, 'macro avg': {'precision': 0.7036560772611811, 'recall': 0.5363961557117422, 'f1-score': 0.5513086799171919, 'support': 30917.0}, 'weighted avg': {'precision': 0.9141947059863795, 'recall': 0.938415758320665, 'f1-score': 0.9173598939731976, 'support': 30917.0}}
Masked Metrics
Masked Accuracy: 0.936109
Masked F1: 0.543085
Masked Classification Report
{'0': {'precision': 0.9403078202995009, 'recall': 0.9949383802816901, 'f1-score': 0.966852010265184, 'support': 13632.0}, '1': {'precision': 0.4772727272727273, 'recall': 0.06818181818181818, 'f1-score': 0.11931818181818182, 'support': 924.0}, 'accuracy': 0.9361088211046991, 'macro avg': {'precision': 0.708790273786114, 'recall': 0.5315600992317542, 'f1-score': 0.5430850960416829, 'support': 14556.0}, 'weighted avg': {'precision': 0.9109148259358888, 'recall': 0.9361088211046991, 'f1-score': 0.9130514292343356, 'support': 14556.0}}
