mrp_0.5_seed66_ep4
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 4
Steps: 410
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.079597
Validation Accuracy: 0.939581
Validation F1: 0.602374
Classification Report
{'0': {'precision': 0.9496280273981582, 'recall': 0.9882336891647625, 'f1-score': 0.9685463114617108, 'support': 29321.0}, '1': {'precision': 0.45754716981132076, 'recall': 0.15919037199124728, 'f1-score': 0.2362012987012987, 'support': 1828.0}, 'accuracy': 0.9395807249028861, 'macro avg': {'precision': 0.7035875986047395, 'recall': 0.5737120305780049, 'f1-score': 0.6023738050815047, 'support': 31149.0}, 'weighted avg': {'precision': 0.9207499315469676, 'recall': 0.9395807249028861, 'f1-score': 0.9255681521844937, 'support': 31149.0}}
Masked Metrics
Masked Accuracy: 0.967964
Masked F1: 0.876755
Masked Classification Report
{'0': {'precision': 0.9897416974169742, 'recall': 0.975913258623199, 'f1-score': 0.9827788362890224, 'support': 13742.0}, '1': {'precision': 0.7047279214986619, 'recall': 0.8503767491926802, 'f1-score': 0.7707317073170732, 'support': 929.0}, 'accuracy': 0.967964010633222, 'macro avg': {'precision': 0.847234809457818, 'recall': 0.9131450039079396, 'f1-score': 0.8767552718030478, 'support': 14671.0}, 'weighted avg': {'precision': 0.971693998021697, 'recall': 0.967964010633222, 'f1-score': 0.9693515455239116, 'support': 14671.0}}
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": 66
"dataset": sold
"finetuning_stage": pre
"val_int": 1000
"patience": 3
"skip_empty_rat": True