xlmr-sold_mrp0.75_s13_pre_ep0
xlm-roberta-base Finetuning
Model Description
Base Model: xlm-roberta-base
Intermediate Task: mrp-
Pre-Finetuned Model: None
Training Information
Epochs: 0
Steps: 0
Validation Time: 0.01s
Performance Metrics
Main Metrics
Validation Loss: 0.426241
Validation Accuracy: 0.941697
Validation F1: 0.484987
Classification Report
{'0': {'precision': 0.9416970832391227, 'recall': 1.0, 'f1-score': 0.9699732171077804, 'support': 29154.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1805.0}, 'accuracy': 0.9416970832391227, 'macro avg': {'precision': 0.47084854161956136, 'recall': 0.5, 'f1-score': 0.4849866085538902, 'support': 30959.0}, 'weighted avg': {'precision': 0.8867933965810711, 'recall': 0.9416970832391227, 'f1-score': 0.9134209493704651, 'support': 30959.0}}
Masked Metrics
Masked Accuracy: 0.938218
Masked F1: 0.484062
Masked Classification Report
{'0': {'precision': 0.9382179305294952, 'recall': 1.0, 'f1-score': 0.9681242916509256, 'support': 20501.0}, '1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1350.0}, 'accuracy': 0.9382179305294952, 'macro avg': {'precision': 0.4691089652647476, 'recall': 0.5, 'f1-score': 0.4840621458254628, 'support': 21851.0}, 'weighted avg': {'precision': 0.8802528851670486, 'recall': 0.9382179305294952, 'f1-score': 0.9083115694080649, 'support': 21851.0}}
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": 13
"dataset": sold
"finetuning_stage": pre
"val_int": 10000
"patience": 3
"skip_empty_rat": True