learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Date	Loc	Org	Per	Price	Product	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
No log	1.0	100	0.0346	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39}	{'precision': 0.957983193277311, 'recall': 0.9193548387096774, 'f1': 0.9382716049382716, 'number': 124}	{'precision': 0.9622641509433962, 'recall': 0.864406779661017, 'f1': 0.9107142857142857, 'number': 59}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79}	{'precision': 0.7647058823529411, 'recall': 1.0, 'f1': 0.8666666666666666, 'number': 13}	0.9708	0.9531	0.9619	0.9919
No log	2.0	200	0.0060	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39}	{'precision': 0.968, 'recall': 0.9758064516129032, 'f1': 0.9718875502008033, 'number': 124}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 59}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}	0.9896	0.9922	0.9909	0.9979
No log	3.0	300	0.0013	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 124}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 59}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}	1.0	1.0	1.0	1.0
No log	4.0	400	0.0010	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 124}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 59}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}	1.0	1.0	1.0	1.0
0.0878	5.0	500	0.0009	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 124}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 59}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 13}	1.0	1.0	1.0	1.0

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

huy1211/roberta-finetuned-ner-vi

roberta-finetuned-ner-vi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

huy1211/
roberta-finetuned-ner-vi