---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: bert_uncased_L-2_H-128_A-2_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: 0.00286100001416597
    - name: Accuracy
      type: accuracy
      value: 0.690316379070282
---

<!-- 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_uncased_L-2_H-128_A-2_cola

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6155
- Matthews Correlation: 0.0029
- Accuracy: 0.6903

## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6288        | 1.0   | 34   | 0.6191          | 0.0                  | 0.6913   |
| 0.6087        | 2.0   | 68   | 0.6184          | 0.0                  | 0.6913   |
| 0.6076        | 3.0   | 102  | 0.6176          | 0.0                  | 0.6913   |
| 0.6066        | 4.0   | 136  | 0.6169          | 0.0                  | 0.6913   |
| 0.605         | 5.0   | 170  | 0.6170          | 0.0                  | 0.6913   |
| 0.6018        | 6.0   | 204  | 0.6164          | 0.0                  | 0.6913   |
| 0.5976        | 7.0   | 238  | 0.6163          | 0.0                  | 0.6913   |
| 0.5871        | 8.0   | 272  | 0.6159          | 0.0464               | 0.6922   |
| 0.5824        | 9.0   | 306  | 0.6155          | 0.0029               | 0.6903   |
| 0.5711        | 10.0  | 340  | 0.6198          | 0.0198               | 0.6702   |
| 0.5591        | 11.0  | 374  | 0.6221          | 0.0685               | 0.6721   |
| 0.5496        | 12.0  | 408  | 0.6284          | 0.1240               | 0.6702   |
| 0.5397        | 13.0  | 442  | 0.6350          | 0.1096               | 0.6548   |
| 0.529         | 14.0  | 476  | 0.6423          | 0.0951               | 0.6433   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3