---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_20_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_20_v2_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8167697254513975
    - name: F1
      type: f1
      value: 0.7368757547772963
---

<!-- 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_20_v2_qqp

This model is a fine-tuned version of [Hartunka/tiny_bert_km_20_v2](https://huggingface.co/Hartunka/tiny_bert_km_20_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4227
- Accuracy: 0.8168
- F1: 0.7369
- Combined Score: 0.7768

## 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 | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.497         | 1.0   | 1422  | 0.4556          | 0.7813   | 0.6727 | 0.7270         |
| 0.4091        | 2.0   | 2844  | 0.4252          | 0.8003   | 0.7087 | 0.7545         |
| 0.3508        | 3.0   | 4266  | 0.4284          | 0.8118   | 0.7313 | 0.7716         |
| 0.3022        | 4.0   | 5688  | 0.4227          | 0.8168   | 0.7369 | 0.7768         |
| 0.2622        | 5.0   | 7110  | 0.4398          | 0.8212   | 0.7536 | 0.7874         |
| 0.2268        | 6.0   | 8532  | 0.4587          | 0.8229   | 0.7595 | 0.7912         |
| 0.2005        | 7.0   | 9954  | 0.4909          | 0.8228   | 0.7602 | 0.7915         |
| 0.1759        | 8.0   | 11376 | 0.5125          | 0.8242   | 0.7618 | 0.7930         |
| 0.1564        | 9.0   | 12798 | 0.5787          | 0.8236   | 0.7680 | 0.7958         |


### Framework versions

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