---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_new_no_pretrain_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      config: qqp
      split: validation
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7856047489488004
    - name: F1
      type: f1
      value: 0.6930594900849859
---

<!-- 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_no_pretrain_qqp

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4537
- Accuracy: 0.7856
- F1: 0.6931
- Combined Score: 0.7393

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5037        | 1.0   | 2843  | 0.4537          | 0.7856   | 0.6931 | 0.7393         |
| 0.4066        | 2.0   | 5686  | 0.4549          | 0.7946   | 0.6758 | 0.7352         |
| 0.3367        | 3.0   | 8529  | 0.4630          | 0.7950   | 0.6650 | 0.7300         |
| 0.2876        | 4.0   | 11372 | 0.5279          | 0.8180   | 0.7598 | 0.7889         |
| 0.2498        | 5.0   | 14215 | 0.4857          | 0.8217   | 0.7650 | 0.7933         |
| 0.2371        | 6.0   | 17058 | 0.5113          | 0.8216   | 0.7376 | 0.7796         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3