---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: deberta-v3-xsmall-CoLA
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE COLA
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - name: Matthews Correlation
      type: matthews_correlation
      value: 0.5894856058137782

widget:
  - text: 'The cat sat on the mat.'
    example_title: Correct grammatical sentence
  - text: 'Me and my friend going to the store.'
    example_title: Incorrect subject-verb agreement
  - text: 'I ain''t got no money.'
    example_title: Incorrect verb conjugation and double negative
  - text: 'She don''t like pizza no more.'
    example_title: Incorrect verb conjugation and double negative
  - text: 'They is arriving tomorrow.'
    example_title: Incorrect verb conjugation
---


# deberta-v3-xsmall-CoLA

This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4237
- Matthews Correlation: 0.5895

## Model description

Trying to find a decent optimum between accuracy/quality and inference speed.


```json
{
    "epoch": 3.0,
    "eval_loss": 0.423,
    "eval_matthews_correlation": 0.589,
    "eval_runtime": 5.0422,
    "eval_samples": 1043,
    "eval_samples_per_second": 206.853,
    "eval_steps_per_second": 51.763
}

```

## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 16105
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.3945        | 1.0   | 67   | 0.4323          | 0.5778               |
| 0.3214        | 2.0   | 134  | 0.4237          | 0.5895               |
| 0.3059        | 3.0   | 201  | 0.4636          | 0.5795               |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1