xlm-roberta-base-pre-mrp-14012025-1412-45
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp
Pre-Finetuned Model: None
Training Information
Epochs: 3
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.130448
Validation Accuracy: 0.939503
Validation F1: 0.613252
Classification Report
{'0': {'precision': 0.9464450600184672, 'recall': 0.9915356711003628, 'f1-score': 0.9684658084327389, 'support': 28945.0}, '1': {'precision': 0.5701754385964912, 'recall': 0.1667521806054387, 'f1-score': 0.25803890432711396, 'support': 1949.0}, 'accuracy': 0.9395028160807923, 'macro avg': {'precision': 0.7583102493074791, 'recall': 0.5791439258529008, 'f1-score': 0.6132523563799264, 'support': 30894.0}, 'weighted avg': {'precision': 0.922707457501751, 'recall': 0.9395028160807923, 'f1-score': 0.9236473311846694, 'support': 30894.0}}
Masked Metrics
Masked Accuracy: 0.953535
Masked F1: 0.753241
Masked Classification Report
{'0': {'precision': 0.9609759577655704, 'recall': 0.9905868510075011, 'f1-score': 0.9755567626290059, 'support': 13598.0}, '1': {'precision': 0.7490196078431373, 'recall': 0.41119483315392896, 'f1-score': 0.5309242529534399, 'support': 929.0}, 'accuracy': 0.9535347972740414, 'macro avg': {'precision': 0.8549977828043538, 'recall': 0.7008908420807151, 'f1-score': 0.753240507791223, 'support': 14527.0}, 'weighted avg': {'precision': 0.9474213732623735, 'recall': 0.9535347972740414, 'f1-score': 0.9471225641373283, 'support': 14527.0}}
