xlm-roberta-base-pre-mrp-14012025-1357-43
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp
Pre-Finetuned Model: None
Training Information
Epochs: 4
Steps: 409
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.027856
Validation Accuracy: 0.943811
Validation F1: 0.583970
Classification Report
{'0': {'precision': 0.952100317585044, 'recall': 0.9904294812846974, 'f1-score': 0.9708867521367521, 'support': 29361.0}, '1': {'precision': 0.43232323232323233, 'recall': 0.12760882528324388, 'f1-score': 0.19705340699815838, 'support': 1677.0}, 'accuracy': 0.9438108125523552, 'macro avg': {'precision': 0.6922117749541381, 'recall': 0.5590191532839707, 'f1-score': 0.5839700795674553, 'support': 31038.0}, 'weighted avg': {'precision': 0.924016479322783, 'recall': 0.9438108125523552, 'f1-score': 0.9290761161486916, 'support': 31038.0}}
Masked Metrics
Masked Accuracy: 0.990004
Masked F1: 0.950744
Masked Classification Report
{'0': {'precision': 0.9936406995230525, 'recall': 0.9957995365005794, 'f1-score': 0.9947189466830645, 'support': 13808.0}, '1': {'precision': 0.9244791666666666, 'recall': 0.8897243107769424, 'f1-score': 0.9067688378033205, 'support': 798.0}, 'accuracy': 0.9900041079008627, 'macro avg': {'precision': 0.9590599330948595, 'recall': 0.9427619236387609, 'f1-score': 0.9507438922431926, 'support': 14606.0}, 'weighted avg': {'precision': 0.9898620535406208, 'recall': 0.9900041079008627, 'f1-score': 0.9899137853188282, 'support': 14606.0}}
