---
language:
- en
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: output
  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: 0.7060783174788182
---

<!-- 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. -->

# output

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3123
- Matthews Correlation: 0.7061

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.3546        | 1.0   | 535  | 0.3123          | 0.7061               |
| 0.2078        | 2.0   | 1070 | 0.3618          | 0.7311               |
| 0.1313        | 3.0   | 1605 | 0.5145          | 0.7160               |
| 0.087         | 4.0   | 2140 | 0.5819          | 0.7230               |
| 0.0597        | 5.0   | 2675 | 0.6325          | 0.7397               |
| 0.0435        | 6.0   | 3210 | 0.6152          | 0.7332               |
| 0.0268        | 7.0   | 3745 | 0.7296          | 0.7327               |
| 0.0304        | 8.0   | 4280 | 0.7672          | 0.7287               |
| 0.015         | 9.0   | 4815 | 0.8067          | 0.7264               |
| 0.0133        | 10.0  | 5350 | 0.8079          | 0.7246               |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0