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Vs2882/liar_binaryclassifier_roberta_base

sourceHugging Facemitupdated 2y agoView on Hugging Face
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Model Card

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liarbinaryclassifierroberta_base

This model is a fine-tuned version of roberta-base on the liar dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6621
  • —Model Preparation Time: 0.0069
  • —Accuracy: 0.5770

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: 3e-06
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 5

Training results

Training LossEpochStepValidation LossModel Preparation TimeAccuracy
0.69341.04610.68430.00690.5553
0.68592.09220.68150.00690.5531
0.67743.013830.66660.00690.5597
0.66714.018440.67420.00690.5748
0.65965.023050.66210.00690.5770

Framework versions

  • —Transformers 4.44.2
  • —Pytorch 2.4.1+cu121
  • —Datasets 3.0.0
  • —Tokenizers 0.19.1