testing_img_token

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: 0.9187
• Eading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
• Ext: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}
• Ub heading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}
• Overall Precision: 0.0
• Overall Recall: 0.0
• Overall F1: 0.0
• Overall Accuracy: 0.4848

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: 0.0005
• 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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Eading	Ext	Ub heading	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
1.4635	1.43	10	1.2178	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}	0.0	0.0	0.0	0.4848
1.2206	2.86	20	1.0016	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}	0.0	0.0	0.0	0.4848
1.0569	4.29	30	0.9783	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}	0.0	0.0	0.0	0.4848
1.0201	5.71	40	0.9273	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}	0.0	0.0	0.0	0.4848
0.9888	7.14	50	0.9187	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}	0.0	0.0	0.0	0.4848

Framework versions

• Transformers 4.26.1
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.2