---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_10_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.82883997031907
    - name: F1
      type: f1
      value: 0.7734119187950229
---

<!-- 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_10_v1_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v1](https://huggingface.co/Hartunka/bert_base_rand_10_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3889
- Accuracy: 0.8288
- F1: 0.7734
- Combined Score: 0.8011

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4757        | 1.0   | 1422  | 0.4247          | 0.7962   | 0.7029 | 0.7495         |
| 0.3697        | 2.0   | 2844  | 0.3917          | 0.8153   | 0.7582 | 0.7868         |
| 0.2939        | 3.0   | 4266  | 0.3889          | 0.8288   | 0.7734 | 0.8011         |
| 0.2329        | 4.0   | 5688  | 0.4264          | 0.8376   | 0.7722 | 0.8049         |
| 0.1847        | 5.0   | 7110  | 0.4509          | 0.8404   | 0.7807 | 0.8106         |
| 0.1492        | 6.0   | 8532  | 0.4776          | 0.8399   | 0.7801 | 0.8100         |
| 0.122         | 7.0   | 9954  | 0.5778          | 0.8429   | 0.7829 | 0.8129         |
| 0.1009        | 8.0   | 11376 | 0.5849          | 0.8363   | 0.7872 | 0.8117         |


### Framework versions

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