pytorch tensorboard fnet text-classification en dataset:glue transformers generated_from_trainer license:apache-2.0 model-index
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: fnet-large-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: 0.0
---

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# fnet-large-finetuned-cola

This model is a fine-tuned version of [google/fnet-large](https://huggingface.co/google/fnet-large) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6243
- Matthews Correlation: 0.0

## 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: 1e-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 | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.6195        | 1.0   | 2138 | 0.6527          | 0.0                  |
| 0.6168        | 2.0   | 4276 | 0.6259          | 0.0                  |
| 0.616         | 3.0   | 6414 | 0.6243          | 0.0                  |


### Framework versions

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