---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_new_pretrain_w_init_48_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: 0.8218896858768241
    - name: F1
      type: f1
      value: 0.7658287535364704
---

<!-- 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_w_init_48_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4082
- Accuracy: 0.8219
- F1: 0.7658
- Combined Score: 0.7939

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5585        | 1.0   | 2843  | 0.5073          | 0.7522   | 0.6429 | 0.6976         |
| 0.4735        | 2.0   | 5686  | 0.4584          | 0.7848   | 0.6963 | 0.7405         |
| 0.4044        | 3.0   | 8529  | 0.4140          | 0.8074   | 0.7234 | 0.7654         |
| 0.3583        | 4.0   | 11372 | 0.4206          | 0.8058   | 0.7602 | 0.7830         |
| 0.3271        | 5.0   | 14215 | 0.4082          | 0.8219   | 0.7658 | 0.7939         |
| 0.2987        | 6.0   | 17058 | 0.4203          | 0.8177   | 0.7666 | 0.7921         |
| 0.3287        | 7.0   | 19901 | 0.4641          | 0.8124   | 0.7209 | 0.7667         |
| 0.3594        | 8.0   | 22744 | 0.4493          | 0.8010   | 0.7246 | 0.7628         |
| 0.3729        | 9.0   | 25587 | 0.4443          | 0.8047   | 0.7388 | 0.7718         |
| 0.3314        | 10.0  | 28430 | 0.4196          | 0.8132   | 0.7411 | 0.7771         |


### Framework versions

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