transformers pytorch tensorboard data2vec-text text-classification generated_from_trainer dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: mit
metrics:
- matthews_correlation
tags:
- generated_from_trainer
model-index:
- name: data2vec-text-base-finetuned-cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.5214716883534575
      name: Matthews Correlation
---

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# data2vec-text-base-finetuned-cola

This model is a fine-tuned version of [facebook/data2vec-text-base](https://huggingface.co/facebook/data2vec-text-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5254
- Matthews Correlation: 0.5215

## 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: 7.160701759709141e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.5632        | 1.0   | 535  | 0.5252          | 0.3869               |
| 0.4572        | 2.0   | 1070 | 0.5534          | 0.4758               |
| 0.3905        | 3.0   | 1605 | 0.4962          | 0.5259               |
| 0.3592        | 4.0   | 2140 | 0.5254          | 0.5215               |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
