mrp_0.5_seed42_b16_e5_radam_s42_msk0.5_ep5
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 5
Steps: 410
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.093199
Validation Accuracy: 0.935699
Validation F1: 0.602955
Classification Report
{'0': {'precision': 0.948051948051948, 'recall': 0.9855351976856316, 'f1-score': 0.9664302600472813, 'support': 29036.0}, '1': {'precision': 0.42701227830832195, 'recall': 0.16640085061137694, 'f1-score': 0.2394797245600612, 'support': 1881.0}, 'accuracy': 0.9356988064818709, 'macro avg': {'precision': 0.687532113180135, 'recall': 0.5759680241485042, 'f1-score': 0.6029549923036712, 'support': 30917.0}, 'weighted avg': {'precision': 0.9163517307350104, 'recall': 0.9356988064818709, 'f1-score': 0.9222023609221572, 'support': 30917.0}}
Masked Metrics
Masked Accuracy: 0.965719
Masked F1: 0.830906
Masked Classification Report
{'0': {'precision': 0.97372588540167, 'recall': 0.9901910548276115, 'f1-score': 0.981889449424745, 'support': 13661.0}, '1': {'precision': 0.7981927710843374, 'recall': 0.5921787709497207, 'f1-score': 0.6799230275817832, 'support': 895.0}, 'accuracy': 0.9657186040120912, 'macro avg': {'precision': 0.8859593282430037, 'recall': 0.7911849128886661, 'f1-score': 0.8309062385032642, 'support': 14556.0}, 'weighted avg': {'precision': 0.9629329383479456, 'recall': 0.9657186040120912, 'f1-score': 0.9633225390407487, '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