mrp_0.5_seed43_ep0
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: 0.535437
Validation Accuracy: 0.945969
Validation F1: 0.486117
Classification Report
{'0': {'precision': 0.9459694567948965, 'recall': 1.0, 'f1-score': 0.9722346396463517, 'support': 29361.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1677.0}, 'accuracy': 0.9459694567948965, 'macro avg': {'precision': 0.47298472839744826, 'recall': 0.5, 'f1-score': 0.48611731982317585, 'support': 31038.0}, 'weighted avg': {'precision': 0.8948582131888316, 'recall': 0.9459694567948965, 'f1-score': 0.9197042739434413, 'support': 31038.0}}
Masked Metrics
Masked Accuracy: 0.943722
Masked F1: 0.485523
Masked Classification Report
{'0': {'precision': 0.9437217581815692, 'recall': 1.0, 'f1-score': 0.9710461430081014, 'support': 13784.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 822.0}, 'accuracy': 0.9437217581815692, 'macro avg': {'precision': 0.4718608790907846, 'recall': 0.5, 'f1-score': 0.4855230715040507, 'support': 14606.0}, 'weighted avg': {'precision': 0.8906107568653122, 'recall': 0.9437217581815692, 'f1-score': 0.916397373355037, 'support': 14606.0}}
Trainer Arguments:
"learning_rate": 2e-05
"epochs": 5
"batch_size": 16
"model": xlm-roberta-base
"intermediate_task": mrp
"n_tk_label": 2
"mask_ratio": 0.5
"seed": 43
"dataset": sold
"finetuning_stage": pre
"val_int": 1000
"patience": 3
"skip_empty_rat": True