---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_rand_20_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8180311649765026
    - name: F1
      type: f1
      value: 0.7436138700121973
---

<!-- 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_rand_20_v1_qqp

This model is a fine-tuned version of [Hartunka/tiny_bert_rand_20_v1](https://huggingface.co/Hartunka/tiny_bert_rand_20_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4170
- Accuracy: 0.8180
- F1: 0.7436
- Combined Score: 0.7808

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4821        | 1.0   | 1422  | 0.4381          | 0.7932   | 0.6989 | 0.7460         |
| 0.3837        | 2.0   | 2844  | 0.4237          | 0.8095   | 0.7141 | 0.7618         |
| 0.3187        | 3.0   | 4266  | 0.4170          | 0.8180   | 0.7436 | 0.7808         |
| 0.2638        | 4.0   | 5688  | 0.4383          | 0.8244   | 0.7517 | 0.7880         |
| 0.2202        | 5.0   | 7110  | 0.4657          | 0.8278   | 0.7575 | 0.7926         |
| 0.1852        | 6.0   | 8532  | 0.5005          | 0.8259   | 0.7641 | 0.7950         |
| 0.1567        | 7.0   | 9954  | 0.5467          | 0.8237   | 0.7665 | 0.7951         |
| 0.1357        | 8.0   | 11376 | 0.5970          | 0.8317   | 0.7599 | 0.7958         |


### Framework versions

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