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# distilbert_add_GLUE_Experiment_logit_kd_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: 1.1264
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 4.3296        | 1.0   | 23   | 3.3387          | nan     | nan       | nan            |
| 3.9535        | 2.0   | 46   | 3.1277          | nan     | nan       | nan            |
| 3.7081        | 3.0   | 69   | 2.9189          | nan     | nan       | nan            |
| 3.4597        | 4.0   | 92   | 2.7125          | nan     | nan       | nan            |
| 3.2232        | 5.0   | 115  | 2.5114          | nan     | nan       | nan            |
| 2.972         | 6.0   | 138  | 2.3156          | 0.0070  | 0.0078    | 0.0074         |
| 2.7373        | 7.0   | 161  | 2.1284          | nan     | nan       | nan            |
| 2.527         | 8.0   | 184  | 1.9503          | nan     | nan       | nan            |
| 2.3016        | 9.0   | 207  | 1.7828          | 0.0092  | 0.0081    | 0.0087         |
| 2.0903        | 10.0  | 230  | 1.6295          | nan     | nan       | nan            |
| 1.8919        | 11.0  | 253  | 1.4932          | -0.0357 | -0.0358   | -0.0358        |
| 1.7184        | 12.0  | 276  | 1.3768          | nan     | nan       | nan            |
| 1.5665        | 13.0  | 299  | 1.2813          | 0.0302  | 0.0292    | 0.0297         |
| 1.4283        | 14.0  | 322  | 1.2075          | 0.0115  | 0.0132    | 0.0123         |
| 1.3175        | 15.0  | 345  | 1.1569          | nan     | nan       | nan            |
| 1.2276        | 16.0  | 368  | 1.1298          | nan     | nan       | nan            |
| 1.1643        | 17.0  | 391  | 1.1264          | nan     | nan       | nan            |
| 1.1172        | 18.0  | 414  | 1.1447          | 0.0009  | 0.0027    | 0.0018         |
| 1.1066        | 19.0  | 437  | 1.1677          | nan     | nan       | nan            |
| 1.1002        | 20.0  | 460  | 1.1712          | 0.0024  | 0.0003    | 0.0014         |
| 1.1027        | 21.0  | 483  | 1.1767          | nan     | nan       | nan            |
| 1.0984        | 22.0  | 506  | 1.1799          | nan     | nan       | nan            |


### 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": "distilbert_add_GLUE_Experiment_logit_kd_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\_logit\_kd\_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: 1.1264
* 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 2.9.0
* 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 2.9.0
* 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 2.9.0
* 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 2.9.0
* Tokenizers 0.13.2