transformers tensorboard safetensors bert text-classification generated_from_trainer en dataset:glue base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google-bert/bert-base-uncased
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased_cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.5683668297227801
      name: Matthews Correlation
    - type: accuracy
      value: 0.8245446085929871
      name: Accuracy
---

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# bert-base-uncased_cola

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4191
- Matthews Correlation: 0.5684
- Accuracy: 0.8245

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.5311        | 1.0   | 34   | 0.4443          | 0.5154               | 0.8035   |
| 0.3306        | 2.0   | 68   | 0.4191          | 0.5684               | 0.8245   |
| 0.2104        | 3.0   | 102  | 0.5792          | 0.5730               | 0.8265   |
| 0.1325        | 4.0   | 136  | 0.5178          | 0.5883               | 0.8322   |
| 0.0962        | 5.0   | 170  | 0.6488          | 0.5779               | 0.8274   |
| 0.0751        | 6.0   | 204  | 0.7336          | 0.5449               | 0.8159   |
| 0.0685        | 7.0   | 238  | 0.7193          | 0.5650               | 0.8236   |


### Framework versions

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