---
language:
- en
base_model: Hartunka/tiny_bert_km_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_100_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7230392156862745
    - name: F1
      type: f1
      value: 0.8197767145135566
---

<!-- 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_mrpc

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 MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5885
- Accuracy: 0.7230
- F1: 0.8198
- Combined Score: 0.7714

## 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 | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6262        | 1.0   | 15   | 0.6086          | 0.6961   | 0.8063 | 0.7512         |
| 0.599         | 2.0   | 30   | 0.6000          | 0.7034   | 0.8191 | 0.7613         |
| 0.5725        | 3.0   | 45   | 0.5969          | 0.7059   | 0.8176 | 0.7618         |
| 0.5494        | 4.0   | 60   | 0.5885          | 0.7230   | 0.8198 | 0.7714         |
| 0.5073        | 5.0   | 75   | 0.6107          | 0.6863   | 0.7808 | 0.7335         |
| 0.4408        | 6.0   | 90   | 0.6365          | 0.7010   | 0.7939 | 0.7474         |
| 0.3565        | 7.0   | 105  | 0.7095          | 0.7108   | 0.8013 | 0.7561         |
| 0.2434        | 8.0   | 120  | 0.8137          | 0.7034   | 0.7939 | 0.7486         |
| 0.1755        | 9.0   | 135  | 0.9716          | 0.6593   | 0.7440 | 0.7017         |


### Framework versions

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