---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_10_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_10_v2_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8202572347266881
    - name: F1
      type: f1
      value: 0.7589318294907945
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_base_rand_10_v2_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_10_v2](https://huggingface.co/Hartunka/bert_base_rand_10_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3871
- Accuracy: 0.8203
- F1: 0.7589
- Combined Score: 0.7896

## 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 | 0.4355          | 0.7913   | 0.6756 | 0.7335         |
| 0.3701        | 2.0   | 2844 | 0.3871          | 0.8203   | 0.7589 | 0.7896         |
| 0.294         | 3.0   | 4266 | 0.3957          | 0.8242   | 0.7747 | 0.7995         |
| 0.2331        | 4.0   | 5688 | 0.4476          | 0.8343   | 0.7689 | 0.8016         |
| 0.1845        | 5.0   | 7110 | 0.4730          | 0.8396   | 0.7799 | 0.8098         |
| 0.1496        | 6.0   | 8532 | 0.4950          | 0.8421   | 0.7814 | 0.8118         |
| 0.1215        | 7.0   | 9954 | 0.6163          | 0.8422   | 0.7848 | 0.8135         |


### Framework versions

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