xlmr-sold_mrp0.1_s13_pre_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: 0.129996
Validation Accuracy: 0.944992
Validation F1: 0.591356
Classification Report
{'0': {'precision': 0.9484724718183304, 'recall': 0.9956781230705907, 'f1-score': 0.9715022005053632, 'support': 29154.0}, '1': {'precision': 0.6440677966101694, 'recall': 0.12631578947368421, 'f1-score': 0.2112088930060213, 'support': 1805.0}, 'accuracy': 0.9449917632998481, 'macro avg': {'precision': 0.79627013421425, 'recall': 0.5609969562721374, 'f1-score': 0.5913555467556922, 'support': 30959.0}, 'weighted avg': {'precision': 0.9307247913780471, 'recall': 0.9449917632998481, 'f1-score': 0.9271748830843769, 'support': 30959.0}}
Masked Metrics
Masked Accuracy: 0.955905
Masked F1: 0.785164
Masked Classification Report
{'0': {'precision': 0.9705882352941176, 'recall': 0.9828641370869033, 'f1-score': 0.9766876140279749, 'support': 2451.0}, '1': {'precision': 0.6666666666666666, 'recall': 0.535031847133758, 'f1-score': 0.5936395759717314, 'support': 157.0}, 'accuracy': 0.9559049079754601, 'macro avg': {'precision': 0.8186274509803921, 'recall': 0.7589479921103306, 'f1-score': 0.7851635949998532, 'support': 2608.0}, 'weighted avg': {'precision': 0.9522923433176952, 'recall': 0.9559049079754601, 'f1-score': 0.9536283571357854, 'support': 2608.0}}
Trainer Arguments:
"learning_rate": 2e-05
"epochs": 5
"batch_size": 16
"model": xlm-roberta-base
"intermediate_task": mrp
"n_tk_label": 2
"mask_ratio": 0.1
"seed": 13
"dataset": sold
"finetuning_stage": pre
"val_int": 10000
"patience": 3
"skip_empty_rat": True