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tmnam20/xlm-roberta-base-vtoc-100

sourceHugging Facemitupdated 3y agoView on Hugging Face
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xlm-roberta-base-vtoc-100

This model is a fine-tuned version of xlm-roberta-base on the tmnam20/VieGLUE/VTOC dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6151
  • —Accuracy: 0.8285

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: 32
  • —evalbatchsize: 16
  • —seed: 100
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 3.0

Training results

Training LossEpochStepValidation LossAccuracy
0.51612.195000.62850.8274

Framework versions

  • —Transformers 4.35.2
  • —Pytorch 2.2.0.dev20231203+cu121
  • —Datasets 2.15.0
  • —Tokenizers 0.15.0