transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 base_model:finetune:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48
datasets:
- glue
language:
- en
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_w_init_48_ver2_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: 0.7573831313381153
      name: Accuracy
    - type: f1
      value: 0.6486622013682438
      name: F1
---

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# hBERTv2_new_pretrain_w_init_48_ver2_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: 0.5073
- Accuracy: 0.7574
- F1: 0.6487
- Combined Score: 0.7030

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5438        | 1.0   | 5686  | 0.5073          | 0.7574   | 0.6487 | 0.7030         |
| 0.5215        | 2.0   | 11372 | 0.5411          | 0.7379   | 0.6475 | 0.6927         |
| 0.5467        | 3.0   | 17058 | 0.6578          | 0.6323   | 0.0047 | 0.3185         |
| 0.5441        | 4.0   | 22744 | 0.5636          | 0.7429   | 0.5943 | 0.6686         |
| 0.5524        | 5.0   | 28430 | 0.5958          | 0.7216   | 0.5353 | 0.6284         |
| 0.5635        | 6.0   | 34116 | 0.5578          | 0.7358   | 0.5946 | 0.6652         |


### Framework versions

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