---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_olda_book_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_olda_book_10_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8799901063566659
    - name: F1
      type: f1
      value: 0.841251145138071
---

<!-- 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_tiny_olda_book_10_v1_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_olda_book_10_v1](https://huggingface.co./gokulsrinivasagan/bert_tiny_olda_book_10_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2816
- Accuracy: 0.8800
- F1: 0.8413
- Combined Score: 0.8606

## 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 OptimizerNames.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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3941        | 1.0   | 1422  | 0.3365          | 0.8496   | 0.7836 | 0.8166         |
| 0.2912        | 2.0   | 2844  | 0.2905          | 0.8710   | 0.8323 | 0.8516         |
| 0.2365        | 3.0   | 4266  | 0.2816          | 0.8800   | 0.8413 | 0.8606         |
| 0.1917        | 4.0   | 5688  | 0.2965          | 0.8807   | 0.8349 | 0.8578         |
| 0.157         | 5.0   | 7110  | 0.3086          | 0.8831   | 0.8474 | 0.8653         |
| 0.1268        | 6.0   | 8532  | 0.3240          | 0.8849   | 0.8496 | 0.8672         |
| 0.1053        | 7.0   | 9954  | 0.3513          | 0.8878   | 0.8496 | 0.8687         |
| 0.0878        | 8.0   | 11376 | 0.3817          | 0.8864   | 0.8520 | 0.8692         |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1