without-cq / README.md
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without-cq
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metadata
license: apache-2.0
base_model: indolem/indobertweet-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: without-cq
    results: []

without-cq

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

  • Loss: 2.1785
  • Accuracy: 0.6604
  • Precision: 0.6734
  • Recall: 0.6604
  • F1: 0.6643

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: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.0888 1.0 266 1.9147 0.6660 0.6707 0.6660 0.6668
0.0379 2.0 532 2.1358 0.6566 0.6523 0.6566 0.6525
0.0568 3.0 798 2.1785 0.6604 0.6734 0.6604 0.6643

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1