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# distilbert_add_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: 2.2529
- Pearson: nan
- Spearmanr: nan
- Combined Score: nan

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 8.7243        | 1.0   | 23   | 6.6928          | nan     | nan       | nan            |
| 7.9215        | 2.0   | 46   | 6.2710          | nan     | nan       | nan            |
| 7.4296        | 3.0   | 69   | 5.8601          | nan     | nan       | nan            |
| 6.9483        | 4.0   | 92   | 5.4460          | nan     | nan       | nan            |
| 6.4768        | 5.0   | 115  | 5.0440          | nan     | nan       | nan            |
| 5.9658        | 6.0   | 138  | 4.6523          | nan     | nan       | nan            |
| 5.5067        | 7.0   | 161  | 4.2735          | nan     | nan       | nan            |
| 5.0622        | 8.0   | 184  | 3.9107          | nan     | nan       | nan            |
| 4.6133        | 9.0   | 207  | 3.5725          | nan     | nan       | nan            |
| 4.2011        | 10.0  | 230  | 3.2630          | nan     | nan       | nan            |
| 3.7839        | 11.0  | 253  | 2.9896          | nan     | nan       | nan            |
| 3.4525        | 12.0  | 276  | 2.7549          | 0.0063  | 0.0066    | 0.0064         |
| 3.1246        | 13.0  | 299  | 2.5637          | -0.0161 | -0.0155   | -0.0158        |
| 2.8674        | 14.0  | 322  | 2.4155          | nan     | nan       | nan            |
| 2.6317        | 15.0  | 345  | 2.3138          | nan     | nan       | nan            |
| 2.4623        | 16.0  | 368  | 2.2596          | nan     | nan       | nan            |
| 2.3397        | 17.0  | 391  | 2.2529          | nan     | nan       | nan            |
| 2.2455        | 18.0  | 414  | 2.2910          | nan     | nan       | nan            |
| 2.1984        | 19.0  | 437  | 2.3424          | nan     | nan       | nan            |
| 2.1869        | 20.0  | 460  | 2.3424          | nan     | nan       | nan            |
| 2.1982        | 21.0  | 483  | 2.3460          | nan     | nan       | nan            |
| 2.195         | 22.0  | 506  | 2.3664          | -0.0023 | 0.0002    | -0.0011        |


### 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_add_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": NaN, "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\_add\_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: 2.2529
* Pearson: nan
* Spearmanr: nan
* Combined Score: nan


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