---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_5_v2_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8173880781597823
    - name: F1
      type: f1
      value: 0.7595192339011758
---

<!-- 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. -->

# bert_base_rand_5_v2_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_5_v2](https://huggingface.co/Hartunka/bert_base_rand_5_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3907
- Accuracy: 0.8174
- F1: 0.7595
- Combined Score: 0.7885

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4731        | 1.0   | 1422 | 0.4262          | 0.7942   | 0.6965 | 0.7453         |
| 0.3673        | 2.0   | 2844 | 0.3907          | 0.8174   | 0.7595 | 0.7885         |
| 0.2918        | 3.0   | 4266 | 0.4051          | 0.8279   | 0.7746 | 0.8013         |
| 0.2294        | 4.0   | 5688 | 0.4142          | 0.8363   | 0.7705 | 0.8034         |
| 0.1819        | 5.0   | 7110 | 0.4686          | 0.8400   | 0.7795 | 0.8097         |
| 0.146         | 6.0   | 8532 | 0.5030          | 0.8407   | 0.7827 | 0.8117         |
| 0.1182        | 7.0   | 9954 | 0.5409          | 0.8411   | 0.7835 | 0.8123         |


### Framework versions

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