---
license: apache-2.0
tags:
- classification
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: sentence-acceptability
  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: 0.8216682646212847
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sentence-acceptability

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: 0.8257
- Accuracy: 0.8217

## Model description

This model classifies English sentences according to two different labels: 1 if the sentence is grammatically acceptable and 0 if the sentence is grammatically unacceptable.


## Training and evaluation data

The model was trained on the "cola" split of the glue dataset, using the 8551 instances of its "train" split. 
For the evaluation, the 1043 sentences of the "evaluation" split were used.



### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4868        | 1.0   | 1069 | 0.6279          | 0.7862   |
| 0.3037        | 2.0   | 2138 | 0.6184          | 0.8140   |
| 0.177         | 3.0   | 3207 | 0.8257          | 0.8217   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2