---
language:
- en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_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: 0.7601038832550087
    - name: F1
      type: f1
      value: 0.6952012821721505
---

<!-- 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. -->

# hBERTv1_new_pretrain_w_init_48_ver2_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4918
- Accuracy: 0.7601
- F1: 0.6952
- Combined Score: 0.7277

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5279        | 1.0   | 5686  | 0.4918          | 0.7601   | 0.6952 | 0.7277         |
| 0.4826        | 2.0   | 11372 | 0.5367          | 0.7644   | 0.6556 | 0.7100         |
| 0.4943        | 3.0   | 17058 | 0.5223          | 0.7594   | 0.6440 | 0.7017         |
| 0.492         | 4.0   | 22744 | 0.5379          | 0.7600   | 0.6465 | 0.7032         |
| 0.505         | 5.0   | 28430 | 0.5431          | 0.7423   | 0.6507 | 0.6965         |
| 0.5428        | 6.0   | 34116 | 0.5789          | 0.7089   | 0.6289 | 0.6689         |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1