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# mobilebert_sa_GLUE_Experiment_logit_kd_pretrain_stsb

This model is a fine-tuned version of [gokuls/mobilebert_sa_pre-training-complete](https://huggingface.co/gokuls/mobilebert_sa_pre-training-complete) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2919
- Pearson: 0.8665
- Spearmanr: 0.8642
- Combined Score: 0.8654

## 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: 5e-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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.1501        | 1.0   | 45   | 0.4726          | 0.7774  | 0.7922    | 0.7848         |
| 0.364         | 2.0   | 90   | 0.3480          | 0.8457  | 0.8455    | 0.8456         |
| 0.259         | 3.0   | 135  | 0.3156          | 0.8582  | 0.8590    | 0.8586         |
| 0.2054        | 4.0   | 180  | 0.4231          | 0.8551  | 0.8549    | 0.8550         |
| 0.1629        | 5.0   | 225  | 0.3245          | 0.8668  | 0.8654    | 0.8661         |
| 0.1263        | 6.0   | 270  | 0.3192          | 0.8649  | 0.8625    | 0.8637         |
| 0.1021        | 7.0   | 315  | 0.3337          | 0.8655  | 0.8629    | 0.8642         |
| 0.0841        | 8.0   | 360  | 0.3061          | 0.8601  | 0.8577    | 0.8589         |
| 0.0713        | 9.0   | 405  | 0.3600          | 0.8576  | 0.8555    | 0.8566         |
| 0.0587        | 10.0  | 450  | 0.3135          | 0.8620  | 0.8600    | 0.8610         |
| 0.0488        | 11.0  | 495  | 0.3006          | 0.8641  | 0.8620    | 0.8631         |
| 0.0441        | 12.0  | 540  | 0.3308          | 0.8645  | 0.8621    | 0.8633         |
| 0.0385        | 13.0  | 585  | 0.3468          | 0.8620  | 0.8601    | 0.8610         |
| 0.0346        | 14.0  | 630  | 0.3175          | 0.8658  | 0.8634    | 0.8646         |
| 0.0298        | 15.0  | 675  | 0.2919          | 0.8665  | 0.8642    | 0.8654         |
| 0.0299        | 16.0  | 720  | 0.3103          | 0.8649  | 0.8628    | 0.8639         |
| 0.0263        | 17.0  | 765  | 0.3325          | 0.8620  | 0.8599    | 0.8609         |
| 0.0237        | 18.0  | 810  | 0.3092          | 0.8636  | 0.8611    | 0.8623         |
| 0.0213        | 19.0  | 855  | 0.3169          | 0.8653  | 0.8631    | 0.8642         |
| 0.0196        | 20.0  | 900  | 0.2985          | 0.8647  | 0.8624    | 0.8636         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["spearmanr"], "model-index": [{"name": "mobilebert_sa_GLUE_Experiment_logit_kd_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": 0.8642221596976783, "name": "Spearmanr"}]}]}]}
transformers pytorch tensorboard mobilebert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

mobilebert\_sa\_GLUE\_Experiment\_logit\_kd\_pretrain\_stsb
===========================================================


This model is a fine-tuned version of gokuls/mobilebert\_sa\_pre-training-complete on the GLUE STSB dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2919
* Pearson: 0.8665
* Spearmanr: 0.8642
* Combined Score: 0.8654


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: 5e-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 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mobilebert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.9.0
* Tokenizers 0.13.2