CoolFace
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gechim/metadata-cls_15_10

sourceHugging Faceagpl-3.0updated 2y agoView on Hugging Face
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Model Card

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metadata-cls1510

This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0128
  • Accuracy: 0.9967
  • F1: 0.9932

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
  • trainbatchsize: 64
  • evalbatchsize: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 15

Training results

Training LossEpochStepValidation LossAccuracyF1
0.52731.00671500.23130.93840.8468
0.23122.01343000.14560.95810.9182
0.15423.02014500.09440.97470.9471
0.11994.02686000.07470.98100.9600
0.09435.03367500.06400.98270.9608
0.08376.04039000.04580.98940.9748
0.06457.047010500.04350.98940.9767
0.05098.053712000.03130.99250.9819
0.0439.060413500.02420.99440.9859
0.034510.067115000.01960.99540.9904
0.0311.073816500.01790.99560.9913
0.023112.080518000.01620.99580.9914
0.022713.087219500.01370.99660.9930
0.018114.094021000.01280.99670.9932

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.20.1