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# hBERTv1_no_pretrain_qqp

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4402
- Accuracy: 0.7954
- F1: 0.7269
- Combined Score: 0.7612

## 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: 96
- eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5334        | 1.0   | 3791  | 0.4826          | 0.7676   | 0.6650 | 0.7163         |
| 0.4491        | 2.0   | 7582  | 0.4493          | 0.7909   | 0.6926 | 0.7417         |
| 0.3866        | 3.0   | 11373 | 0.4402          | 0.7954   | 0.7269 | 0.7612         |
| 0.3657        | 4.0   | 15164 | 0.4990          | 0.7775   | 0.7211 | 0.7493         |
| 0.3708        | 5.0   | 18955 | 0.4744          | 0.8077   | 0.7273 | 0.7675         |
| 0.2948        | 6.0   | 22746 | 0.4693          | 0.8143   | 0.7379 | 0.7761         |
| 0.2546        | 7.0   | 26537 | 0.4507          | 0.8120   | 0.7578 | 0.7849         |
| 0.2225        | 8.0   | 30328 | 0.5245          | 0.8193   | 0.7511 | 0.7852         |


### Framework versions

- Transformers 4.30.2
- 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": "hBERTv1_no_pretrain_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": 0.7953747217412812, "name": "Accuracy"}, {"type": "f1", "value": 0.7269366603954186, "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 

hBERTv1\_no\_pretrain\_qqp
==========================


This model is a fine-tuned version of [](URL on the GLUE QQP dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4402
* Accuracy: 0.7954
* F1: 0.7269
* Combined Score: 0.7612


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: 96
* eval\_batch\_size: 96
* 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 4.30.2
* 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: 96
* eval\_batch\_size: 96
* 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 4.30.2
* 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: 96
* eval\_batch\_size: 96
* 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 4.30.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3