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yaziedmoh/disabilityy_model_final

sourceHugging Faceupdated 1y agoView on Hugging Face
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Model Card

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disabilityymodelfinal

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7063
  • Accuracy: 0.9993
  • F1: 0.9993

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
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 10
  • labelsmoothingfactor: 0.1

Training results

Training LossEpochStepValidation LossAccuracyF1
3.32420.13611002.90160.55100.4600
2.10470.27212001.73080.91090.9011
1.33160.40823001.07830.97760.9773
0.92190.54424000.81200.99050.9905
0.76270.68035000.74480.99390.9939
0.73250.81636000.73460.99590.9959
0.72390.95247000.72230.99800.9980
0.71371.08848000.71820.99800.9980
0.7111.22459000.71750.99660.9966
0.71031.360510000.71390.99860.9986
0.70881.496611000.71340.99730.9973
0.7081.632712000.71310.99730.9973
0.70711.768713000.71020.99800.9980
0.70561.904814000.70960.99860.9986
0.70932.040815000.70810.99930.9993
0.70462.176916000.70690.99930.9993
0.7052.312917000.70630.99930.9993
0.70352.449018000.70630.99930.9993
0.70412.585019000.70710.99930.9993
0.70332.721120000.70650.99930.9993

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.1