
<!-- 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_w_init__qqp

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3996
- Accuracy: 0.8135
- F1: 0.7339
- Combined Score: 0.7737

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5075        | 1.0   | 2843  | 0.4451          | 0.7864   | 0.7172 | 0.7518         |
| 0.4118        | 2.0   | 5686  | 0.4144          | 0.8052   | 0.7377 | 0.7715         |
| 0.3583        | 3.0   | 8529  | 0.3996          | 0.8135   | 0.7339 | 0.7737         |
| 0.3174        | 4.0   | 11372 | 0.4160          | 0.8195   | 0.7566 | 0.7880         |
| 0.2918        | 5.0   | 14215 | 0.4424          | 0.8142   | 0.7633 | 0.7888         |
| 0.2769        | 6.0   | 17058 | 0.4765          | 0.8195   | 0.7583 | 0.7889         |
| 0.2576        | 7.0   | 19901 | 0.4033          | 0.8237   | 0.7675 | 0.7956         |
| 0.2327        | 8.0   | 22744 | 0.4414          | 0.8279   | 0.7682 | 0.7981         |


### 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": "hBERTv1_new_pretrain_w_init__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": 0.8135295572594607, "name": "Accuracy"}, {"type": "f1", "value": 0.7339332980412917, "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\_new\_pretrain\_w\_init\_\_qqp
======================================


This model is a fine-tuned version of gokuls/bert\_12\_layer\_model\_v1\_complete\_training\_new\_wt\_init on the GLUE QQP dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3996
* Accuracy: 0.8135
* F1: 0.7339
* Combined Score: 0.7737


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