text-classification / README.md
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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: text-classification
    results: []

text-classification

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9158
  • Accuracy: 0.7695

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: 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0037 1.0 499 1.0119 0.7024
0.7645 2.0 998 0.9929 0.7275
0.6417 3.0 1497 0.9623 0.7335
0.8177 4.0 1996 0.9158 0.7695
0.4176 5.0 2495 1.2640 0.7635
0.7335 6.0 2994 1.2080 0.7615
0.3151 7.0 3493 1.3485 0.7575
0.7147 8.0 3992 1.2736 0.7605
0.0728 9.0 4491 1.4076 0.7565
0.2183 10.0 4990 1.5012 0.7505
0.2202 11.0 5489 1.5981 0.7405
0.2694 12.0 5988 1.5516 0.7415
0.0497 13.0 6487 1.6425 0.7485
0.2473 14.0 6986 1.7087 0.7475
0.1949 15.0 7485 1.6820 0.7535
0.1233 16.0 7984 1.7447 0.7405
0.0632 17.0 8483 1.7229 0.7475
0.1161 18.0 8982 1.7292 0.7545
0.0023 19.0 9481 1.7930 0.7465
0.0854 20.0 9980 1.8089 0.7495

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1