README.md

metadata

license: mit
base_model: SCUT-DLVCLab/lilt-roberta-en-base
tags:
  - generated_from_trainer
model-index:
  - name: Data_extraction
    results: []

Data_extraction

This model is a fine-tuned version of SCUT-DLVCLab/lilt-roberta-en-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• Ign: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}
• Overall Precision: 1.0
• Overall Recall: 1.0
• Overall F1: 1.0
• Overall Accuracy: 1.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 2500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Ign	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
0.032	18.1818	200	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	36.3636	400	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	54.5455	600	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	72.7273	800	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	90.9091	1000	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	109.0909	1200	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	127.2727	1400	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	145.4545	1600	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	163.6364	1800	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	181.8182	2000	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	200.0	2200	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0
0.0	218.1818	2400	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 6933}	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1