---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: bert_base_km_5_v2_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: 0.006434621036303265
    - name: Accuracy
      type: accuracy
      value: 0.6864812970161438
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_base_km_5_v2_cola

This model is a fine-tuned version of [Hartunka/bert_base_km_5_v2](https://huggingface.co/Hartunka/bert_base_km_5_v2) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6109
- Matthews Correlation: 0.0064
- Accuracy: 0.6865

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6153        | 1.0   | 34   | 0.6196          | 0.0                  | 0.6913   |
| 0.5911        | 2.0   | 68   | 0.6109          | 0.0064               | 0.6865   |
| 0.5354        | 3.0   | 102  | 0.6187          | 0.0696               | 0.6817   |
| 0.4723        | 4.0   | 136  | 0.6894          | 0.0819               | 0.6587   |
| 0.4026        | 5.0   | 170  | 0.7198          | 0.1243               | 0.6577   |
| 0.3374        | 6.0   | 204  | 0.7933          | 0.1073               | 0.6347   |
| 0.2903        | 7.0   | 238  | 0.9325          | 0.0947               | 0.6366   |


### Framework versions

- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1