transformers pytorch tensorboard bert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: sa_BERT_24_cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.0
      name: Matthews Correlation
    - type: accuracy
      value: 0.6912751793861389
      name: Accuracy
---

<!-- 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. -->

# sa_BERT_24_cola

This model is a fine-tuned version of [gokuls/bert_base_24](https://huggingface.co/gokuls/bert_base_24) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6120
- Matthews Correlation: 0.0
- Accuracy: 0.6913

## 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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6138        | 1.0   | 90   | 0.6120          | 0.0                  | 0.6913   |
| 0.5898        | 2.0   | 180  | 0.6242          | 0.0656               | 0.6932   |
| 0.5491        | 3.0   | 270  | 0.6798          | 0.0733               | 0.6405   |
| 0.5027        | 4.0   | 360  | 0.6873          | 0.0667               | 0.6328   |
| 0.4549        | 5.0   | 450  | 0.7841          | 0.1025               | 0.6299   |
| 0.4177        | 6.0   | 540  | 0.8221          | 0.0827               | 0.5849   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
