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# hBERTv2_new_pretrain_48_qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4029
- Accuracy: 0.8216
- F1: 0.7562
- Combined Score: 0.7889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5044        | 1.0   | 2843  | 0.4468          | 0.7865   | 0.6961 | 0.7413         |
| 0.4102        | 2.0   | 5686  | 0.4359          | 0.7992   | 0.6935 | 0.7464         |
| 0.3553        | 3.0   | 8529  | 0.4127          | 0.8080   | 0.7105 | 0.7592         |
| 0.3122        | 4.0   | 11372 | 0.4029          | 0.8216   | 0.7562 | 0.7889         |
| 0.2756        | 5.0   | 14215 | 0.4481          | 0.8228   | 0.7518 | 0.7873         |
| 0.2479        | 6.0   | 17058 | 0.4778          | 0.8268   | 0.7633 | 0.7951         |
| 0.223         | 7.0   | 19901 | 0.4425          | 0.8158   | 0.7721 | 0.7939         |
| 0.2028        | 8.0   | 22744 | 0.4705          | 0.8267   | 0.7686 | 0.7977         |
| 0.183         | 9.0   | 25587 | 0.4908          | 0.8301   | 0.7659 | 0.7980         |


### Framework versions

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

{"language": ["en"], "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "hBERTv2_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": 0.8216176106851348, "name": "Accuracy"}, {"type": "f1", "value": 0.7561536380849337, "name": "F1"}]}]}]}
transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #hybridbert #text-classification #generated_from_trainer #en #dataset-glue #model-index #autotrain_compatible #endpoints_compatible #region-us 

hBERTv2\_new\_pretrain\_48\_qqp
===============================


This model is a fine-tuned version of gokuls/bert\_12\_layer\_model\_v2\_complete\_training\_new\_48 on the GLUE QQP dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4029
* Accuracy: 0.8216
* F1: 0.7562
* Combined Score: 0.7889


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



### Framework versions


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



### 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 ### Framework versions


* Transformers 4.29.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #hybridbert #text-classification #generated_from_trainer #en #dataset-glue #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


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