---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_100_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_100_v2_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.817932228543161
    - name: F1
      type: f1
      value: 0.755489121408404
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_base_rand_100_v2_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_100_v2](https://huggingface.co/Hartunka/bert_base_rand_100_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3863
- Accuracy: 0.8179
- F1: 0.7555
- Combined Score: 0.7867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4754        | 1.0   | 1422 | 0.4311          | 0.7961   | 0.6978 | 0.7470         |
| 0.3723        | 2.0   | 2844 | 0.3863          | 0.8179   | 0.7555 | 0.7867         |
| 0.2962        | 3.0   | 4266 | 0.3932          | 0.8259   | 0.7750 | 0.8005         |
| 0.2334        | 4.0   | 5688 | 0.4347          | 0.8354   | 0.7769 | 0.8061         |
| 0.1823        | 5.0   | 7110 | 0.4591          | 0.8375   | 0.7768 | 0.8072         |
| 0.1443        | 6.0   | 8532 | 0.4977          | 0.8385   | 0.7738 | 0.8061         |
| 0.1156        | 7.0   | 9954 | 0.5663          | 0.8370   | 0.7841 | 0.8105         |


### Framework versions

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