---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: roberta-base-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: 0.6232164195970928
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8456375838926175
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.843528494100156
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.8456375838926175
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.8450074516171895
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.7826539226919134
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.8456375838926175
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.8456375838926175
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.8032750971481726
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.8456375838926175
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.838197890972622
      verified: true
    - name: loss
      type: loss
      value: 1.0575031042099
      verified: true
---

<!-- 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. -->

# roberta-base-cola

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0571
- Matthews Correlation: 0.6232

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.5497        | 1.0   | 535  | 0.5504          | 0.4613               |
| 0.3786        | 2.0   | 1070 | 0.4850          | 0.5470               |
| 0.2733        | 3.0   | 1605 | 0.5036          | 0.5792               |
| 0.2204        | 4.0   | 2140 | 0.5532          | 0.6139               |
| 0.164         | 5.0   | 2675 | 0.9516          | 0.5934               |
| 0.1351        | 6.0   | 3210 | 0.9051          | 0.5754               |
| 0.1065        | 7.0   | 3745 | 0.9006          | 0.6161               |
| 0.0874        | 8.0   | 4280 | 0.9457          | 0.6157               |
| 0.0579        | 9.0   | 4815 | 1.0372          | 0.6007               |
| 0.0451        | 10.0  | 5350 | 1.0571          | 0.6232               |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1