---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_20_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_rand_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: 0.7999010635666585
    - name: F1
      type: f1
      value: 0.7081108385048348
---

<!-- 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_v2_qqp

This model is a fine-tuned version of [Hartunka/tiny_bert_rand_20_v2](https://huggingface.co/Hartunka/tiny_bert_rand_20_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4248
- Accuracy: 0.7999
- F1: 0.7081
- Combined Score: 0.7540

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4957        | 1.0   | 1422 | 0.4587          | 0.7812   | 0.6709 | 0.7260         |
| 0.4075        | 2.0   | 2844 | 0.4248          | 0.7999   | 0.7081 | 0.7540         |
| 0.3493        | 3.0   | 4266 | 0.4263          | 0.8119   | 0.7310 | 0.7714         |
| 0.3035        | 4.0   | 5688 | 0.4371          | 0.8148   | 0.7284 | 0.7716         |
| 0.2653        | 5.0   | 7110 | 0.4532          | 0.8201   | 0.7490 | 0.7846         |
| 0.2333        | 6.0   | 8532 | 0.4573          | 0.8225   | 0.7554 | 0.7890         |
| 0.2073        | 7.0   | 9954 | 0.4749          | 0.8237   | 0.7656 | 0.7947         |


### Framework versions

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