mrp_0.5_seed42_aug_ep2
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 2
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.193125
Validation Accuracy: 0.939160
Validation F1: 0.484313
Classification Report
{'0': {'precision': 0.9391596856098586, 'recall': 1.0, 'f1-score': 0.9686254232482111, 'support': 29036.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1881.0}, 'accuracy': 0.9391596856098586, 'macro avg': {'precision': 0.4695798428049293, 'recall': 0.5, 'f1-score': 0.48431271162410555, 'support': 30917.0}, 'weighted avg': {'precision': 0.8820209150748085, 'recall': 0.9391596856098586, 'f1-score': 0.9096939479715063, 'support': 30917.0}}
Masked Metrics
Masked Accuracy: 0.934254
Masked F1: 0.483005
Masked Classification Report
{'0': {'precision': 0.9342539159109645, 'recall': 1.0, 'f1-score': 0.966009589770911, 'support': 13599.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 957.0}, 'accuracy': 0.9342539159109645, 'macro avg': {'precision': 0.46712695795548226, 'recall': 0.5, 'f1-score': 0.4830047948854555, 'support': 14556.0}, 'weighted avg': {'precision': 0.8728303793949717, 'recall': 0.9342539159109645, 'f1-score': 0.902498242051018, 'support': 14556.0}}
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": 42
"dataset": sold
"finetuning_stage": pre
"val_int": 10000
"patience": 3
"skip_empty_rat": True