This model is a fine-tuned version of
cahya/NusaBert-v1.3
on the grit-id/id_nergrit_corpus ner dataset.
It achieves the following results on the evaluation set:
Loss: 0.2174
Precision: 0.8010
Recall: 0.8338
F1: 0.8171
Accuracy: 0.9477
Model description
The dataset contains 19 following entities
'CRD': Cardinal
'DAT': Date
'EVT': Event
'FAC': Facility
'GPE': Geopolitical Entity
'LAW': Law Entity (such as Undang-Undang)
'LOC': Location
'MON': Money
'NOR': Political Organization
'ORD': Ordinal
'ORG': Organization
'PER': Person
'PRC': Percent
'PRD': Product
'QTY': Quantity
'REG': Religion
'TIM': Time
'WOA': Work of Art
'LAN': Language
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: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 64
total_eval_batch_size: 64
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: 3.0
Training results
Framework versions
Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 2.19.2
Tokenizers 0.21.0
Runs of cahya NusaBert-ner-v1.3 on huggingface.co
657
Total runs
-9
24-hour runs
-47
3-day runs
-51
7-day runs
320
30-day runs
More Information About NusaBert-ner-v1.3 huggingface.co Model
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