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# hBERTv1_new_pretrain_mrpc

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6018
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6855        | 1.0   | 29   | 0.6255          | 0.6838   | 0.8122 | 0.7480         |
| 0.647         | 2.0   | 58   | 0.6536          | 0.6838   | 0.8122 | 0.7480         |
| 0.6336        | 3.0   | 87   | 0.6537          | 0.6838   | 0.8122 | 0.7480         |
| 0.6007        | 4.0   | 116  | 0.6018          | 0.6838   | 0.8122 | 0.7480         |
| 0.5196        | 5.0   | 145  | 0.6852          | 0.6544   | 0.7273 | 0.6908         |
| 0.3703        | 6.0   | 174  | 0.7167          | 0.6838   | 0.7709 | 0.7273         |
| 0.2697        | 7.0   | 203  | 0.9072          | 0.7010   | 0.7953 | 0.7481         |
| 0.1997        | 8.0   | 232  | 1.0467          | 0.6765   | 0.7651 | 0.7208         |
| 0.1629        | 9.0   | 261  | 1.0809          | 0.6593   | 0.7495 | 0.7044         |


### 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_mrpc", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE MRPC", "type": "glue", "config": "mrpc", "split": "validation", "args": "mrpc"}, "metrics": [{"type": "accuracy", "value": 0.6838235294117647, "name": "Accuracy"}, {"type": "f1", "value": 0.8122270742358079, "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\_mrpc
============================


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


* Loss: 0.6018
* Accuracy: 0.6838
* F1: 0.8122
* Combined Score: 0.7480


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