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# add_BERT_no_pretrain_stsb

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3307
- Pearson: 0.0719
- Spearmanr: 0.0575
- Combined Score: 0.0647

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.4937        | 1.0   | 45   | 2.6373          | 0.0410  | 0.0287    | 0.0348         |
| 2.22          | 2.0   | 90   | 2.4288          | 0.0740  | 0.0586    | 0.0663         |
| 2.1554        | 3.0   | 135  | 2.3869          | 0.0609  | 0.0498    | 0.0554         |
| 2.0556        | 4.0   | 180  | 2.5740          | 0.0800  | 0.0717    | 0.0759         |
| 2.0221        | 5.0   | 225  | 2.4656          | 0.0849  | 0.0654    | 0.0752         |
| 2.0403        | 6.0   | 270  | 2.3307          | 0.0719  | 0.0575    | 0.0647         |
| 2.1732        | 7.0   | 315  | 2.5174          | 0.0699  | 0.0584    | 0.0641         |
| 2.0399        | 8.0   | 360  | 2.5648          | 0.0718  | 0.0605    | 0.0662         |
| 2.0765        | 9.0   | 405  | 2.3373          | 0.0621  | 0.0491    | 0.0556         |
| 2.0538        | 10.0  | 450  | 2.6402          | 0.0463  | 0.0431    | 0.0447         |
| 2.0147        | 11.0  | 495  | 2.4727          | 0.0540  | 0.0471    | 0.0506         |


### 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": ["spearmanr"], "model-index": [{"name": "add_BERT_no_pretrain_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": 0.05749928795262334, "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 

add\_BERT\_no\_pretrain\_stsb
=============================


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


* Loss: 2.3307
* Pearson: 0.0719
* Spearmanr: 0.0575
* Combined Score: 0.0647


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