metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: fnet-large-finetuned-mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8259803921568627
          - name: F1
            type: f1
            value: 0.8798646362098139

fnet-large-finetuned-mrpc

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

Loss: 1.0872
Accuracy: 0.8260
F1: 0.8799
Combined Score: 0.8529

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	F1	Combined Score
0.5656	1.0	917	0.6999	0.7843	0.8581	0.8212
0.3874	2.0	1834	0.7280	0.8088	0.8691	0.8390
0.1627	3.0	2751	1.1274	0.8162	0.8780	0.8471
0.0751	4.0	3668	1.0289	0.8333	0.8870	0.8602
0.0339	5.0	4585	1.0872	0.8260	0.8799	0.8529

Framework versions

Transformers 4.11.0.dev0
Pytorch 1.9.0
Datasets 1.12.1
Tokenizers 0.10.3