Edit model card

indobert-model-ner

This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2296
  • Precision: 0.8307
  • Recall: 0.8454
  • F1: 0.8380
  • Accuracy: 0.9530

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.4855 1.0 784 0.1729 0.8069 0.8389 0.8226 0.9499
0.1513 2.0 1568 0.1781 0.8086 0.8371 0.8226 0.9497
0.1106 3.0 2352 0.1798 0.8231 0.8475 0.8351 0.9531
0.0784 4.0 3136 0.1941 0.8270 0.8442 0.8355 0.9535
0.0636 5.0 3920 0.2085 0.8269 0.8514 0.8389 0.9548
0.0451 6.0 4704 0.2296 0.8307 0.8454 0.8380 0.9530

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
20
Safetensors
Model size
110M params
Tensor type
F32
·

Finetuned from