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# hBERTv1_new_pretrain_48_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5726
- Pearson: 0.5712
- Spearmanr: 0.5660
- Combined Score: 0.5686

## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.4091        | 1.0   | 45   | 2.3547          | 0.1191  | 0.1028    | 0.1109         |
| 2.0478        | 2.0   | 90   | 2.4073          | 0.1413  | 0.1417    | 0.1415         |
| 1.8232        | 3.0   | 135  | 2.2454          | 0.2345  | 0.2627    | 0.2486         |
| 1.3631        | 4.0   | 180  | 1.9067          | 0.4891  | 0.4765    | 0.4828         |
| 1.2243        | 5.0   | 225  | 2.2429          | 0.4693  | 0.4507    | 0.4600         |
| 0.9081        | 6.0   | 270  | 1.7410          | 0.5250  | 0.5197    | 0.5224         |
| 0.7373        | 7.0   | 315  | 1.5726          | 0.5712  | 0.5660    | 0.5686         |
| 0.5958        | 8.0   | 360  | 1.8736          | 0.5183  | 0.5104    | 0.5143         |
| 0.5189        | 9.0   | 405  | 2.2244          | 0.5154  | 0.5137    | 0.5146         |
| 0.4191        | 10.0  | 450  | 1.8942          | 0.5165  | 0.5105    | 0.5135         |
| 0.3765        | 11.0  | 495  | 1.7040          | 0.5749  | 0.5652    | 0.5700         |
| 0.3326        | 12.0  | 540  | 1.7679          | 0.5656  | 0.5625    | 0.5641         |


### 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": ["spearmanr"], "model-index": [{"name": "hBERTv1_new_pretrain_48_stsb", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE STSB", "type": "glue", "config": "stsb", "split": "validation", "args": "stsb"}, "metrics": [{"type": "spearmanr", "value": 0.5659522242277619, "name": "Spearmanr"}]}]}]}
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\_48\_stsb
================================


This model is a fine-tuned version of gokuls/bert\_12\_layer\_model\_v1\_complete\_training\_new\_48 on the GLUE STSB dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5726
* Pearson: 0.5712
* Spearmanr: 0.5660
* Combined Score: 0.5686


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