---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_50_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_km_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: 0.824387830818699
    - name: F1
      type: f1
      value: 0.7619686200885074
---

<!-- 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_km_50_v2_qqp

This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3899
- Accuracy: 0.8244
- F1: 0.7620
- Combined Score: 0.7932

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4831        | 1.0   | 1422  | 0.4464          | 0.7857   | 0.6639 | 0.7248         |
| 0.3789        | 2.0   | 2844  | 0.3969          | 0.8142   | 0.7440 | 0.7791         |
| 0.3007        | 3.0   | 4266  | 0.3899          | 0.8244   | 0.7620 | 0.7932         |
| 0.2341        | 4.0   | 5688  | 0.4301          | 0.8297   | 0.7578 | 0.7937         |
| 0.18          | 5.0   | 7110  | 0.4499          | 0.8295   | 0.7779 | 0.8037         |
| 0.1381        | 6.0   | 8532  | 0.5405          | 0.8346   | 0.7790 | 0.8068         |
| 0.1072        | 7.0   | 9954  | 0.5882          | 0.8326   | 0.7779 | 0.8052         |
| 0.0866        | 8.0   | 11376 | 0.5793          | 0.8286   | 0.7794 | 0.8040         |


### Framework versions

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