README.md

metadata

library_name: transformers
license: mit
base_model: vinai/phobert-large
tags:
  - generated_from_trainer
model-index:
  - name: grab-ner-ghtk-ai-fluent-segmented-21-label-new-data-3090-6Obt-1
    results: []

grab-ner-ghtk-ai-fluent-segmented-21-label-new-data-3090-6Obt-1

This model is a fine-tuned version of vinai/phobert-large on the None dataset.

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: 2.5e-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
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Ho	Hoảng thời gian	Háng trừu tượng	Hông tin ctt	Hụ cấp	Hứ	Iấy tờ	Iền cụ thể	Iền trừu tượng	à số thuế	à đơn	Ình thức làm việc	Ông	Ương	Ị trí	Ố công	Ố giờ	Ố điểm	Ố đơn	Ợt	Ỷ lệ	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
No log	1.0	147	0.4119	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6}	{'precision': 0.5657894736842105, 'recall': 0.6825396825396826, 'f1': 0.6187050359712231, 'number': 63}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}	{'precision': 0.26865671641791045, 'recall': 0.43902439024390244, 'f1': 0.3333333333333333, 'number': 82}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 54}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 16}	{'precision': 0.6808510638297872, 'recall': 0.9411764705882353, 'f1': 0.7901234567901235, 'number': 238}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 42}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}	{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}	0.5622	0.4864	0.5215	0.8912

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1