---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_48_KD_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: 0.8117487014593124
    - name: F1
      type: f1
      value: 0.7245086328591595
---

<!-- 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_48_KD_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48_KD](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48_KD) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4106
- Accuracy: 0.8117
- F1: 0.7245
- Combined Score: 0.7681

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5016        | 1.0   | 2843  | 0.4533          | 0.7776   | 0.6963 | 0.7370         |
| 0.4125        | 2.0   | 5686  | 0.4433          | 0.8023   | 0.7269 | 0.7646         |
| 0.3574        | 3.0   | 8529  | 0.4106          | 0.8117   | 0.7245 | 0.7681         |
| 0.3134        | 4.0   | 11372 | 0.4395          | 0.8208   | 0.7461 | 0.7834         |
| 0.279         | 5.0   | 14215 | 0.4975          | 0.8236   | 0.7627 | 0.7931         |
| 0.248         | 6.0   | 17058 | 0.5527          | 0.8129   | 0.7066 | 0.7598         |
| 0.2215        | 7.0   | 19901 | 0.4814          | 0.8209   | 0.7697 | 0.7953         |
| 0.1998        | 8.0   | 22744 | 0.4820          | 0.8272   | 0.7702 | 0.7987         |


### Framework versions

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