---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: distilbert_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: 0.06558874629318973
    - name: Accuracy
      type: accuracy
      value: 0.693192720413208
---

<!-- 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. -->

# distilbert_km_5_v2_cola

This model is a fine-tuned version of [Hartunka/distilbert_km_5_v2](https://huggingface.co/Hartunka/distilbert_km_5_v2) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6176
- Matthews Correlation: 0.0656
- Accuracy: 0.6932

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6134        | 1.0   | 34   | 0.6176          | 0.0656               | 0.6932   |
| 0.5825        | 2.0   | 68   | 0.6216          | 0.0445               | 0.6884   |
| 0.5309        | 3.0   | 102  | 0.6439          | 0.0643               | 0.6721   |
| 0.4729        | 4.0   | 136  | 0.7091          | 0.1182               | 0.6894   |
| 0.413         | 5.0   | 170  | 0.7330          | 0.1260               | 0.6405   |
| 0.3505        | 6.0   | 204  | 0.8545          | 0.0740               | 0.6242   |


### Framework versions

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