mrp_0.1_seed66_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: 0.752062
Validation Accuracy: 0.058975
Validation F1: 0.055776
Classification Report
{'0': {'precision': 0.8, 'recall': 0.00040926298557347973, 'f1-score': 0.0008181074447777475, 'support': 29321.0}, '1': {'precision': 0.0586175884884692, 'recall': 0.9983588621444202, 'f1-score': 0.11073357199199078, 'support': 1828.0}, 'accuracy': 0.05897460592635398, 'macro avg': {'precision': 0.4293087942442346, 'recall': 0.49938406256499684, 'f1-score': 0.05577583971838426, 'support': 31149.0}, 'weighted avg': {'precision': 0.7564914749031084, 'recall': 0.05897460592635398, 'f1-score': 0.007268570355057545, 'support': 31149.0}}
Masked Metrics
Masked Accuracy: 0.067348
Masked F1: 0.063831
Masked Classification Report
{'0': {'precision': 1.0, 'recall': 0.003234937323089365, 'f1-score': 0.006449012494961709, 'support': 2473.0}, '1': {'precision': 0.06451612903225806, 'recall': 1.0, 'f1-score': 0.12121212121212122, 'support': 170.0}, 'accuracy': 0.06734771093454407, 'macro avg': {'precision': 0.532258064516129, 'recall': 0.5016174686615447, 'f1-score': 0.06383056685354146, 'support': 2643.0}, 'weighted avg': {'precision': 0.9398288845764222, 'recall': 0.06734771093454407, 'f1-score': 0.013830672911880783, 'support': 2643.0}}
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": 66
"dataset": sold
"finetuning_stage": pre
"val_int": 1000
"patience": 3
"skip_empty_rat": True