Edit model card

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
Downloads last month
2,167
Safetensors
Model size
277M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Pavarissy/phayathaibert-thainer

Finetuned
(9)
this model

Dataset used to train Pavarissy/phayathaibert-thainer

Collection including Pavarissy/phayathaibert-thainer