---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_100_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8215186742517933
    - name: F1
      type: f1
      value: 0.7754263662392631
---

<!-- 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_v1_qqp

This model is a fine-tuned version of [Hartunka/bert_base_rand_100_v1](https://huggingface.co/Hartunka/bert_base_rand_100_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3942
- Accuracy: 0.8215
- F1: 0.7754
- Combined Score: 0.7985

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4745        | 1.0   | 1422  | 0.4387          | 0.7917   | 0.6787 | 0.7352         |
| 0.3731        | 2.0   | 2844  | 0.3947          | 0.8202   | 0.7488 | 0.7845         |
| 0.2984        | 3.0   | 4266  | 0.3942          | 0.8215   | 0.7754 | 0.7985         |
| 0.2356        | 4.0   | 5688  | 0.4295          | 0.8370   | 0.7676 | 0.8023         |
| 0.1843        | 5.0   | 7110  | 0.4590          | 0.8408   | 0.7762 | 0.8085         |
| 0.1461        | 6.0   | 8532  | 0.5344          | 0.8405   | 0.7784 | 0.8095         |
| 0.1169        | 7.0   | 9954  | 0.5650          | 0.8414   | 0.7836 | 0.8125         |
| 0.0952        | 8.0   | 11376 | 0.5598          | 0.8357   | 0.7854 | 0.8105         |


### Framework versions

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