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Tung177/deberta-v3-base-finetuned-context_relevance_judge

sourceHugging Facemitupdated 2y agoView on Hugging Face
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deberta-v3-base-finetuned-contextrelevancejudge

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 6.6398
  • —Accuracy: 0.3418

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-06
  • —trainbatchsize: 2
  • —evalbatchsize: 16
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 32
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracy
No log0.992931.66780.0
No log1.99731874.05650.2880
No log2.9922806.14610.2846
No log3.99733745.97170.3461
No log4.9924676.43120.3327
0.14695.99735616.51530.3410
0.14696.9926546.63980.3418

Framework versions

  • —Transformers 4.46.3
  • —Pytorch 2.4.0
  • —Datasets 3.1.0
  • —Tokenizers 0.20.3