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fifadxj/tiny-bert-sequence-classification

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

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tiny-bert-sequence-classification

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

  • —Loss: 0.3375
  • —Accuracy: 0.9467
  • —Precision: 0.9491
  • —Recall: 0.9427
  • —F1: 0.9459

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: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 10
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1
0.35781.01500.20340.92420.91690.93090.9238
0.16772.03000.17310.94420.97470.91060.9416
0.09323.04500.19170.94420.96960.91570.9419
0.05554.06000.19040.95170.96520.93590.9503
0.03125.07500.22700.950.96350.93420.9486
0.02186.09000.26190.95250.96530.93760.9512
0.0147.010500.33160.94670.96160.92920.9451
0.00948.012000.33750.94670.94910.94270.9459

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.8.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1