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# distilbert_sa_GLUE_Experiment_stsb_96

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2501
- Pearson: 0.0145
- Spearmanr: 0.0164
- Combined Score: 0.0154

## 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: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 8.5764        | 1.0   | 23   | 6.5600          | -0.0093 | -0.0112   | -0.0102        |
| 7.7973        | 2.0   | 46   | 6.1824          | 0.0235  | 0.0229    | 0.0232         |
| 7.3288        | 3.0   | 69   | 5.7819          | -0.0634 | -0.0621   | -0.0628        |
| 6.8588        | 4.0   | 92   | 5.3627          | nan     | nan       | nan            |
| 6.3722        | 5.0   | 115  | 4.9405          | nan     | nan       | nan            |
| 5.8419        | 6.0   | 138  | 4.5257          | 0.0099  | 0.0107    | 0.0103         |
| 5.3405        | 7.0   | 161  | 4.1302          | nan     | nan       | nan            |
| 4.8794        | 8.0   | 184  | 3.7607          | nan     | nan       | nan            |
| 4.4156        | 9.0   | 207  | 3.4218          | -0.0075 | -0.0067   | -0.0071        |
| 3.991         | 10.0  | 230  | 3.1190          | 0.0246  | 0.0246    | 0.0246         |
| 3.6029        | 11.0  | 253  | 2.8558          | -0.0034 | -0.0006   | -0.0020        |
| 3.2636        | 12.0  | 276  | 2.6377          | nan     | nan       | nan            |
| 2.9656        | 13.0  | 299  | 2.4660          | 0.0137  | 0.0129    | 0.0133         |
| 2.7028        | 14.0  | 322  | 2.3432          | nan     | nan       | nan            |
| 2.4851        | 15.0  | 345  | 2.2710          | 0.0132  | 0.0145    | 0.0138         |
| 2.3576        | 16.0  | 368  | 2.2501          | 0.0145  | 0.0164    | 0.0154         |
| 2.2531        | 17.0  | 391  | 2.2773          | nan     | nan       | nan            |
| 2.2045        | 18.0  | 414  | 2.3342          | -0.0082 | -0.0113   | -0.0098        |
| 2.1967        | 19.0  | 437  | 2.3460          | nan     | nan       | nan            |
| 2.2041        | 20.0  | 460  | 2.3556          | -0.0025 | -0.0010   | -0.0017        |
| 2.1816        | 21.0  | 483  | 2.3715          | 0.0142  | 0.0160    | 0.0151         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["spearmanr"], "model-index": [{"name": "distilbert_sa_GLUE_Experiment_stsb_96", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "GLUE STSB", "type": "glue", "config": "stsb", "split": "validation", "args": "stsb"}, "metrics": [{"type": "spearmanr", "value": 0.01641373482271163, "name": "Spearmanr"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #en #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert\_sa\_GLUE\_Experiment\_stsb\_96
==========================================


This model is a fine-tuned version of distilbert-base-uncased on the GLUE STSB dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2501
* Pearson: 0.0145
* Spearmanr: 0.0164
* Combined Score: 0.0154


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: 256
* eval\_batch\_size: 256
* 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
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.8.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 256
* eval\_batch\_size: 256
* 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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 256
* eval\_batch\_size: 256
* 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
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.8.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #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: 256
* eval\_batch\_size: 256
* 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
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.14.0a0+410ce96
* Datasets 2.8.0
* Tokenizers 0.13.2