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Librarian Bot: Add base_model information to model (#2)
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: cahya/distilbert-base-indonesian
model-index:
  - name: DistilBERT-Hoax-Detection
    results: []

DistilBERT-Hoax-Detection

This model is a fine-tuned version of cahya/distilbert-base-indonesian on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5261
  • Accuracy: 0.8441

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-06
  • 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
  • lr_scheduler_warmup_ratio: 0.15
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6644 1.0 93 0.6368 0.6237
0.4151 2.0 186 0.5300 0.7258
0.3645 3.0 279 0.5003 0.7688
0.3283 4.0 372 0.4585 0.7957
0.2557 5.0 465 0.4599 0.8065
0.3993 6.0 558 0.5004 0.8065
0.0536 7.0 651 0.4658 0.8387
0.1944 8.0 744 0.5264 0.8280
0.0612 9.0 837 0.5195 0.8387
0.0602 10.0 930 0.5261 0.8441

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3