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# add_BERT_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: 0.5939
- Accuracy: 0.6824
- F1: 0.4705
- Combined Score: 0.5764

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.657         | 1.0   | 2843  | 0.6438          | 0.6490   | 0.1608 | 0.4049         |
| 0.6273        | 2.0   | 5686  | 0.6302          | 0.6443   | 0.1919 | 0.4181         |
| 0.6273        | 3.0   | 8529  | 0.6265          | 0.6527   | 0.3602 | 0.5064         |
| 0.6093        | 4.0   | 11372 | 0.5939          | 0.6824   | 0.4705 | 0.5764         |
| 0.5932        | 5.0   | 14215 | 0.5962          | 0.6802   | 0.4170 | 0.5486         |
| 0.599         | 6.0   | 17058 | 0.5981          | 0.6757   | 0.4795 | 0.5776         |
| 0.6063        | 7.0   | 19901 | 0.6511          | 0.6318   | 0.0    | 0.3159         |
| 0.6264        | 8.0   | 22744 | 0.6261          | 0.6532   | 0.2074 | 0.4303         |
| 0.6348        | 9.0   | 25587 | 0.6774          | 0.6318   | 0.0    | 0.3159         |


### 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": "add_BERT_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": 0.6823893148651992, "name": "Accuracy"}, {"type": "f1", "value": 0.4704523897892697, "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 

add\_BERT\_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: 0.5939
* Accuracy: 0.6824
* F1: 0.4705
* Combined Score: 0.5764


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 4.30.2
* 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: 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 4.30.2
* 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: 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 4.30.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3