transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_48_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      config: qqp
      split: validation
      args: qqp
    metrics:
    - type: accuracy
      value: 0.7994063813999506
      name: Accuracy
    - type: f1
      value: 0.7127780138829862
      name: F1
---

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# hBERTv1_new_pretrain_48_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4284
- Accuracy: 0.7994
- F1: 0.7128
- Combined Score: 0.7561

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5134        | 1.0   | 2843  | 0.4628          | 0.7740   | 0.6835 | 0.7288         |
| 0.4312        | 2.0   | 5686  | 0.4284          | 0.7994   | 0.7128 | 0.7561         |
| 0.3732        | 3.0   | 8529  | 0.4313          | 0.8027   | 0.7024 | 0.7525         |
| 0.3281        | 4.0   | 11372 | 0.4352          | 0.8138   | 0.7491 | 0.7814         |
| 0.2908        | 5.0   | 14215 | 0.4482          | 0.8148   | 0.7540 | 0.7844         |
| 0.2592        | 6.0   | 17058 | 0.4526          | 0.8167   | 0.7650 | 0.7909         |
| 0.2355        | 7.0   | 19901 | 0.4539          | 0.8125   | 0.7611 | 0.7868         |


### Framework versions

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