xlm-roberta-base-pre-mrp-14012025-1415-45
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: 0.074879
Validation Accuracy: 0.937884
Validation F1: 0.617143
Classification Report
{'0': {'precision': 0.9470654403493681, 'recall': 0.9889790982898601, 'f1-score': 0.9675685724425817, 'support': 28945.0}, '1': {'precision': 0.5224550898203593, 'recall': 0.17906618778860955, 'f1-score': 0.26671761559037066, 'support': 1949.0}, 'accuracy': 0.9378843788437884, 'macro avg': {'precision': 0.7347602650848637, 'recall': 0.5840226430392348, 'f1-score': 0.6171430940164762, 'support': 30894.0}, 'weighted avg': {'precision': 0.920278181555394, 'recall': 0.9378843788437884, 'f1-score': 0.9233542099480857, 'support': 30894.0}}
Masked Metrics
Masked Accuracy: 0.971088
Masked F1: 0.886183
Masked Classification Report
{'0': {'precision': 0.9874046084315034, 'recall': 0.9815865065920306, 'f1-score': 0.9844869616606338, 'support': 13577.0}, '1': {'precision': 0.7572815533980582, 'recall': 0.8210526315789474, 'f1-score': 0.7878787878787878, 'support': 950.0}, 'accuracy': 0.971088318303848, 'macro avg': {'precision': 0.8723430809147807, 'recall': 0.9013195690854889, 'f1-score': 0.8861828747697108, 'support': 14527.0}, 'weighted avg': {'precision': 0.9723556029739571, 'recall': 0.971088318303848, 'f1-score': 0.9716296776313949, 'support': 14527.0}}
