README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: fnet-large-finetuned-qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8943111550828593
          - name: F1
            type: f1
            value: 0.8556565212985171

fnet-large-finetuned-qqp

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

• Loss: 0.5515
• Accuracy: 0.8943
• F1: 0.8557
• Combined Score: 0.8750

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	F1	Combined Score
0.4574	1.0	90962	0.4946	0.8694	0.8297	0.8496
0.3387	2.0	181924	0.4745	0.8874	0.8437	0.8655
0.2029	3.0	272886	0.5515	0.8943	0.8557	0.8750

Framework versions

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