---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: bert_base_km_5_v1_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: 0.04959298805408078
    - name: Accuracy
      type: accuracy
      value: 0.6874400973320007
---

<!-- 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_base_km_5_v1_cola

This model is a fine-tuned version of [Hartunka/bert_base_km_5_v1](https://huggingface.co/Hartunka/bert_base_km_5_v1) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6169
- Matthews Correlation: 0.0496
- Accuracy: 0.6874

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6154        | 1.0   | 34   | 0.6184          | -0.0079              | 0.6894   |
| 0.5959        | 2.0   | 68   | 0.6171          | 0.0055               | 0.6740   |
| 0.5583        | 3.0   | 102  | 0.6169          | 0.0496               | 0.6874   |
| 0.5145        | 4.0   | 136  | 0.6424          | 0.0953               | 0.6635   |
| 0.4591        | 5.0   | 170  | 0.6875          | 0.0989               | 0.6491   |
| 0.412         | 6.0   | 204  | 0.7451          | 0.0651               | 0.6309   |
| 0.3633        | 7.0   | 238  | 0.7966          | 0.1089               | 0.6203   |
| 0.3189        | 8.0   | 272  | 0.8536          | 0.1002               | 0.6462   |


### Framework versions

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