disfluency-large-2 / README.md
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metadata
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: disfluency-large-2
    results: []

disfluency-large-2

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

  • Loss: 0.0318
  • Precision: 0.9837
  • Recall: 0.9808
  • F1: 0.9822
  • Accuracy: 0.9946

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 140 0.0439 0.9538 0.9561 0.9550 0.9890
No log 2.0 280 0.0314 0.9660 0.9736 0.9698 0.9906
No log 3.0 420 0.0394 0.9710 0.9651 0.9681 0.9909
0.1105 4.0 560 0.0320 0.9795 0.9784 0.9790 0.9929
0.1105 5.0 700 0.0450 0.9704 0.9657 0.9681 0.9904
0.1105 6.0 840 0.0463 0.9776 0.9694 0.9734 0.9911
0.1105 7.0 980 0.0480 0.9706 0.9712 0.9709 0.9909
0.0113 8.0 1120 0.0318 0.9837 0.9808 0.9822 0.9946
0.0113 9.0 1260 0.0419 0.9699 0.9669 0.9684 0.9915
0.0113 10.0 1400 0.0458 0.9735 0.9712 0.9723 0.9920
0.0051 11.0 1540 0.0309 0.9777 0.9766 0.9771 0.9935
0.0051 12.0 1680 0.0232 0.9820 0.9820 0.9820 0.9951
0.0051 13.0 1820 0.0344 0.9849 0.9784 0.9816 0.9945

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3