xlm-roberta-base-pre-mrp-14012025-1407-45
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp
Pre-Finetuned Model: None
Training Information
Epochs: 0
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.641075
Validation Accuracy: 0.905775
Validation F1: 0.519319
Classification Report
{'0': {'precision': 0.9390219224283305, 'recall': 0.9618932458110209, 'f1-score': 0.9503199931734789, 'support': 28945.0}, '1': {'precision': 0.11334405144694534, 'recall': 0.07234479220112879, 'f1-score': 0.08831819605386784, 'support': 1949.0}, 'accuracy': 0.9057745840616301, 'macro avg': {'precision': 0.5261829869376379, 'recall': 0.5171190190060748, 'f1-score': 0.5193190946136734, 'support': 30894.0}, 'weighted avg': {'precision': 0.8869326439100835, 'recall': 0.9057745840616301, 'f1-score': 0.89593915862353, 'support': 30894.0}}
Masked Metrics
Masked Accuracy: 0.922351
Masked F1: 0.489353
Masked Classification Report
{'0': {'precision': 0.9321172457007589, 'recall': 0.9887009822022007, 'f1-score': 0.9595756880733946, 'support': 13541.0}, '1': {'precision': 0.06707317073170732, 'recall': 0.011156186612576065, 'f1-score': 0.019130434782608695, 'support': 986.0}, 'accuracy': 0.9223514834446204, 'macro avg': {'precision': 0.49959520821623316, 'recall': 0.4999285844073884, 'f1-score': 0.4893530614280016, 'support': 14527.0}, 'weighted avg': {'precision': 0.8734035775022675, 'recall': 0.9223514834446204, 'f1-score': 0.8957442693534445, 'support': 14527.0}}
