mrp_0.9_seed66_ep1
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 1
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.215788
Validation Accuracy: 0.938714
Validation F1: 0.525915
Classification Report
{'0': {'precision': 0.9436460154075225, 'recall': 0.9942703182019713, 'f1-score': 0.9682969359794071, 'support': 29321.0}, '1': {'precision': 0.3411764705882353, 'recall': 0.047592997811816196, 'f1-score': 0.08353336533845415, 'support': 1828.0}, 'accuracy': 0.9387139234004301, 'macro avg': {'precision': 0.6424112429978789, 'recall': 0.5209316580068938, 'f1-score': 0.5259151506589307, 'support': 31149.0}, 'weighted avg': {'precision': 0.9082896852547195, 'recall': 0.9387139234004301, 'f1-score': 0.9163739911936464, 'support': 31149.0}}
Masked Metrics
Masked Accuracy: 0.937216
Masked F1: 0.666762
Masked Classification Report
{'0': {'precision': 0.9541489863272041, 'recall': 0.9801428744400048, 'f1-score': 0.9669712715761811, 'support': 24777.0}, '1': {'precision': 0.49382716049382713, 'recall': 0.29143897996357016, 'f1-score': 0.3665521191294387, 'support': 1647.0}, 'accuracy': 0.9372161671207992, 'macro avg': {'precision': 0.7239880734105156, 'recall': 0.6357909272017874, 'f1-score': 0.6667616953528099, 'support': 26424.0}, 'weighted avg': {'precision': 0.9254572648941292, 'recall': 0.9372161671207992, 'f1-score': 0.9295473257663195, 'support': 26424.0}}
Trainer Arguments:
"learning_rate": 2e-05
"epochs": 5
"batch_size": 16
"model": xlm-roberta-base
"intermediate_task": mrp
"n_tk_label": 2
"mask_ratio": 0.9
"seed": 66
"dataset": sold
"finetuning_stage": pre
"val_int": 1000
"patience": 3
"skip_empty_rat": True