---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_new_pretrain_48_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: qqp
      split: validation
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8300766757358398
    - name: F1
      type: f1
      value: 0.7659443990188063
---

<!-- 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. -->

# hBERTv2_new_pretrain_48_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4908
- Accuracy: 0.8301
- F1: 0.7659
- Combined Score: 0.7980

## 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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5044        | 1.0   | 2843  | 0.4468          | 0.7865   | 0.6961 | 0.7413         |
| 0.4102        | 2.0   | 5686  | 0.4359          | 0.7992   | 0.6935 | 0.7464         |
| 0.3553        | 3.0   | 8529  | 0.4127          | 0.8080   | 0.7105 | 0.7592         |
| 0.3122        | 4.0   | 11372 | 0.4029          | 0.8216   | 0.7562 | 0.7889         |
| 0.2756        | 5.0   | 14215 | 0.4481          | 0.8228   | 0.7518 | 0.7873         |
| 0.2479        | 6.0   | 17058 | 0.4778          | 0.8268   | 0.7633 | 0.7951         |
| 0.223         | 7.0   | 19901 | 0.4425          | 0.8158   | 0.7721 | 0.7939         |
| 0.2028        | 8.0   | 22744 | 0.4705          | 0.8267   | 0.7686 | 0.7977         |
| 0.183         | 9.0   | 25587 | 0.4908          | 0.8301   | 0.7659 | 0.7980         |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3