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gchhablani/fnet-large-finetuned-wnli

sourceHugging Faceapache-2.0updated 5y agoView on Hugging Face
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Model Card

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fnet-large-finetuned-wnli

This model is a fine-tuned version of google/fnet-large on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.6953
  • —Accuracy: 0.3803

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: 4
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 5.0

Training results

Training LossEpochStepValidation LossAccuracy
0.72171.01590.68640.5634
0.70562.03180.68690.5634
0.7063.04770.68750.5634
0.70324.06360.69310.5634
0.70255.07950.69530.3803

Framework versions

  • —Transformers 4.11.0.dev0
  • —Pytorch 1.9.0
  • —Datasets 1.12.1
  • —Tokenizers 0.10.3