---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
- matthews_correlation
model-index:
- name: bert-base-uncased-finetuned-glue_cola
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8293384467881112
    - name: F1
      type: f1
      value: 0.820234272230632
    - name: Matthews Correlation
      type: matthews_correlation
      value: 0.5806473000395166
---

<!-- 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. -->

# bert-base-uncased-finetuned-glue_cola

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6466
- Accuracy: 0.8293
- F1: 0.8202
- Matthews Correlation: 0.5806

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------------:|
| 0.5418        | 1.0   | 535  | 0.4594          | 0.8006   | 0.7836 | 0.5019               |
| 0.3635        | 2.0   | 1070 | 0.4437          | 0.8217   | 0.8084 | 0.5600               |
| 0.2019        | 3.0   | 1605 | 0.6466          | 0.8293   | 0.8202 | 0.5806               |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0