---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_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: 0.8430373485035865
    - name: F1
      type: f1
      value: 0.7845307619176966
---

<!-- 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_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: 0.3476
- Accuracy: 0.8430
- F1: 0.7845
- Combined Score: 0.8138

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4637        | 1.0   | 2843  | 0.3907          | 0.8136   | 0.7636 | 0.7886         |
| 0.363         | 2.0   | 5686  | 0.3536          | 0.8338   | 0.7900 | 0.8119         |
| 0.3211        | 3.0   | 8529  | 0.3476          | 0.8430   | 0.7845 | 0.8138         |
| 0.2906        | 4.0   | 11372 | 0.3539          | 0.8531   | 0.8059 | 0.8295         |
| 0.2603        | 5.0   | 14215 | 0.3531          | 0.8531   | 0.8017 | 0.8274         |
| 0.2373        | 6.0   | 17058 | 0.3716          | 0.8561   | 0.8089 | 0.8325         |
| 0.2175        | 7.0   | 19901 | 0.3553          | 0.8565   | 0.8123 | 0.8344         |
| 0.1957        | 8.0   | 22744 | 0.3726          | 0.8551   | 0.8099 | 0.8325         |


### Framework versions

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