---
language:
- en
base_model: Hartunka/tiny_bert_km_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: tiny_bert_km_100_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: 0.0
    - name: Accuracy
      type: accuracy
      value: 0.6912751793861389
---

<!-- 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. -->

# tiny_bert_km_100_v1_cola

This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6238
- Matthews Correlation: 0.0
- Accuracy: 0.6913

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6196        | 1.0   | 34   | 0.6238          | 0.0                  | 0.6913   |
| 0.6075        | 2.0   | 68   | 0.6263          | 0.0                  | 0.6913   |
| 0.5972        | 3.0   | 102  | 0.6293          | 0.0                  | 0.6913   |
| 0.5804        | 4.0   | 136  | 0.6354          | -0.0196              | 0.6683   |
| 0.5561        | 5.0   | 170  | 0.6381          | 0.0361               | 0.6673   |
| 0.5088        | 6.0   | 204  | 0.6593          | 0.0537               | 0.6616   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1