---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_50_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_50_v2_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.827652733118971
    - name: F1
      type: f1
      value: 0.7696833476565083
---

<!-- 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_50_v2_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_50_v2](https://huggingface.co/Hartunka/bert_base_rand_50_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3953
- Accuracy: 0.8277
- F1: 0.7697
- Combined Score: 0.7987

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4729        | 1.0   | 1422  | 0.4349          | 0.7941   | 0.6892 | 0.7416         |
| 0.3717        | 2.0   | 2844  | 0.3957          | 0.8183   | 0.7598 | 0.7890         |
| 0.2951        | 3.0   | 4266  | 0.3953          | 0.8277   | 0.7697 | 0.7987         |
| 0.2327        | 4.0   | 5688  | 0.4646          | 0.8348   | 0.7638 | 0.7993         |
| 0.1833        | 5.0   | 7110  | 0.4751          | 0.8385   | 0.7783 | 0.8084         |
| 0.145         | 6.0   | 8532  | 0.5040          | 0.8344   | 0.7852 | 0.8098         |
| 0.1174        | 7.0   | 9954  | 0.6122          | 0.8348   | 0.7863 | 0.8106         |
| 0.0944        | 8.0   | 11376 | 0.6167          | 0.8388   | 0.7829 | 0.8108         |


### Framework versions

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