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Pavarissy/phayathaibert-thainer
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metadata
base_model: clicknext/phayathaibert
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: phayathaibert-thainer
    results: []

phayathaibert-thainer

This model is a fine-tuned version of clicknext/phayathaibert on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1324
  • Precision: 0.8432
  • Recall: 0.8915
  • F1: 0.8666
  • Accuracy: 0.9735

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: 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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 493 0.1401 0.7300 0.7941 0.7607 0.9607
0.3499 2.0 986 0.1201 0.7863 0.8464 0.8152 0.9688
0.0961 3.0 1479 0.1169 0.8050 0.8663 0.8345 0.9715
0.0617 4.0 1972 0.1137 0.8155 0.8656 0.8398 0.9718
0.0438 5.0 2465 0.1280 0.8201 0.8714 0.8450 0.9725
0.0302 6.0 2958 0.1386 0.8266 0.8730 0.8492 0.9726
0.0239 7.0 3451 0.1401 0.8353 0.8789 0.8565 0.9733
0.0166 8.0 3944 0.1444 0.8356 0.8782 0.8564 0.9738
0.0139 9.0 4437 0.1530 0.8341 0.8785 0.8557 0.9735
0.0106 10.0 4930 0.1508 0.8394 0.8782 0.8583 0.9738

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0