xlm-roberta-base-pre-mrp-14012025-1356-43
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: 0.029807
Validation Accuracy: 0.942748
Validation F1: 0.585829
Classification Report
{'0': {'precision': 0.9523450311577566, 'recall': 0.9889649535097579, 'f1-score': 0.9703096021787438, 'support': 29361.0}, '1': {'precision': 0.40875912408759124, 'recall': 0.13357185450208706, 'f1-score': 0.20134831460674157, 'support': 1677.0}, 'accuracy': 0.9427475997164766, 'macro avg': {'precision': 0.6805520776226739, 'recall': 0.5612684040059225, 'f1-score': 0.5858289583927427, 'support': 31038.0}, 'weighted avg': {'precision': 0.9229747893201167, 'recall': 0.9427475997164766, 'f1-score': 0.9287622061075328, 'support': 31038.0}}
Masked Metrics
Masked Accuracy: 0.989593
Masked F1: 0.950274
Masked Classification Report
{'0': {'precision': 0.9923338395892095, 'recall': 0.9966586765453621, 'f1-score': 0.9944915561353918, 'support': 13767.0}, '1': {'precision': 0.9409499358151476, 'recall': 0.8736591179976162, 'f1-score': 0.9060568603213844, 'support': 839.0}, 'accuracy': 0.9895933178145967, 'macro avg': {'precision': 0.9666418877021785, 'recall': 0.9351588972714892, 'f1-score': 0.9502742082283882, 'support': 14606.0}, 'weighted avg': {'precision': 0.9893822378319564, 'recall': 0.9895933178145967, 'f1-score': 0.9894116773329851, 'support': 14606.0}}
