mrp_0.75_seed66_ep3
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 3
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.195411
Validation Accuracy: 0.941700
Validation F1: 0.509571
Classification Report
{'0': {'precision': 0.9426722889239386, 'recall': 0.9988063162920774, 'f1-score': 0.9699278002252103, 'support': 29321.0}, '1': {'precision': 0.573170731707317, 'recall': 0.025711159737417943, 'f1-score': 0.049214659685863874, 'support': 1828.0}, 'accuracy': 0.9416995730200006, 'macro avg': {'precision': 0.7579215103156278, 'recall': 0.5122587380147476, 'f1-score': 0.509571229955537, 'support': 31149.0}, 'weighted avg': {'precision': 0.9209878416995659, 'recall': 0.9416995730200006, 'f1-score': 0.9158951307685367, 'support': 31149.0}}
Masked Metrics
Masked Accuracy: 0.939062
Masked F1: 0.504309
Masked Classification Report
{'0': {'precision': 0.9398824976089629, 'recall': 0.9989834446703456, 'f1-score': 0.968532206969377, 'support': 20658.0}, '1': {'precision': 0.5714285714285714, 'recall': 0.020771513353115726, 'f1-score': 0.04008589835361489, 'support': 1348.0}, 'accuracy': 0.9390620739798237, 'macro avg': {'precision': 0.7556555345187672, 'recall': 0.5098774790117306, 'f1-score': 0.504309052661496, 'support': 22006.0}, 'weighted avg': {'precision': 0.9173124761379474, 'recall': 0.9390620739798237, 'f1-score': 0.9116592803123722, 'support': 22006.0}}
Trainer Arguments:
"learning_rate": 2e-05
"epochs": 5
"batch_size": 16
"model": xlm-roberta-base
"intermediate_task": mrp
"n_tk_label": 2
"mask_ratio": 0.75
"seed": 66
"dataset": sold
"finetuning_stage": pre
"val_int": 1000
"patience": 3
"skip_empty_rat": True