metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: fnet-large-finetuned-wnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE WNLI
          type: glue
          args: wnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.38028169014084506

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
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: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7217	1.0	159	0.6864	0.5634
0.7056	2.0	318	0.6869	0.5634
0.706	3.0	477	0.6875	0.5634
0.7032	4.0	636	0.6931	0.5634
0.7025	5.0	795	0.6953	0.3803

Framework versions

Transformers 4.11.0.dev0
Pytorch 1.9.0
Datasets 1.12.1
Tokenizers 0.10.3