---
language:
- en
license: apache-2.0
base_model: google/fnet-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-base-finetuned-cola
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - name: Matthews Correlation
      type: matthews_correlation
      value: 0.3262988329908328
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fnet-base-finetuned-cola

This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5648
- Matthews Correlation: 0.3263

## 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: 32
- eval_batch_size: 16
- 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 | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6101        | 1.0   | 268  | 0.6032          | 0.1346               |
| 0.5325        | 2.0   | 536  | 0.5451          | 0.3135               |
| 0.428         | 3.0   | 804  | 0.5648          | 0.3263               |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 1.13.1
- Datasets 2.19.1
- Tokenizers 0.19.1