---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_5_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8229037843185754
    - name: F1
      type: f1
      value: 0.7561474014031742
---

<!-- 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_5_v1_qqp

This model is a fine-tuned version of [Hartunka/tiny_bert_km_5_v1](https://huggingface.co/Hartunka/tiny_bert_km_5_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3982
- Accuracy: 0.8229
- F1: 0.7561
- Combined Score: 0.7895

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4854        | 1.0   | 1422  | 0.4320          | 0.7934   | 0.7100 | 0.7517         |
| 0.3893        | 2.0   | 2844  | 0.4019          | 0.8130   | 0.7421 | 0.7775         |
| 0.3257        | 3.0   | 4266  | 0.3982          | 0.8229   | 0.7561 | 0.7895         |
| 0.2734        | 4.0   | 5688  | 0.4342          | 0.8248   | 0.7447 | 0.7847         |
| 0.2309        | 5.0   | 7110  | 0.4551          | 0.8302   | 0.7638 | 0.7970         |
| 0.1964        | 6.0   | 8532  | 0.4515          | 0.8269   | 0.7721 | 0.7995         |
| 0.1681        | 7.0   | 9954  | 0.4995          | 0.8293   | 0.7751 | 0.8022         |
| 0.146         | 8.0   | 11376 | 0.5505          | 0.8304   | 0.7759 | 0.8031         |


### Framework versions

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