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fnet-large-finetuned-sst2

This model is a fine-tuned version of google/fnet-large on the GLUE SST2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5240
  • Accuracy: 0.9048

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
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.394 1.0 16838 0.3896 0.8968
0.2076 2.0 33676 0.5100 0.8956
0.1148 3.0 50514 0.5240 0.9048

Framework versions

  • Transformers 4.11.0.dev0
  • Pytorch 1.9.0
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Dataset used to train gchhablani/fnet-large-finetuned-sst2

Evaluation results