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domenicrosati/deberta-v3-large-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22

sourceHugging Facemitupdated 4y agoView on Hugging Face
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Model Card

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deberta-v3-large-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22

This model is a fine-tuned version of domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0002
  • —Accuracy: 0.9998
  • —F1: 0.9999

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: 6e-06
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 50
  • —num_epochs: 12
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyF1
0.18841.06690.02480.99510.9964
0.04942.013380.00840.99870.9990
0.01993.020070.00510.99910.9993
0.00794.026760.00300.99930.9995
0.05.033450.00260.99940.9996
0.06.040140.00140.99960.9997
0.07.046830.00150.99960.9997
0.08.053520.00110.99960.9997
0.01439.060210.00001.01.0
0.010.066900.00350.99910.9993
0.011.073590.00040.99980.9999
0.012.080280.00020.99980.9999

Framework versions

  • —Transformers 4.18.0
  • —Pytorch 1.11.0
  • —Datasets 2.1.0
  • —Tokenizers 0.12.1