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# distilbert-base-uncased__sst2__train-16-6

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8356
- Accuracy: 0.6480

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6978        | 1.0   | 7    | 0.6807          | 0.4286   |
| 0.6482        | 2.0   | 14   | 0.6775          | 0.4286   |
| 0.6051        | 3.0   | 21   | 0.6623          | 0.5714   |
| 0.486         | 4.0   | 28   | 0.6710          | 0.5714   |
| 0.4612        | 5.0   | 35   | 0.5325          | 0.7143   |
| 0.2233        | 6.0   | 42   | 0.4992          | 0.7143   |
| 0.1328        | 7.0   | 49   | 0.4753          | 0.7143   |
| 0.0905        | 8.0   | 56   | 0.2416          | 1.0      |
| 0.0413        | 9.0   | 63   | 0.2079          | 1.0      |
| 0.0356        | 10.0  | 70   | 0.2234          | 0.8571   |
| 0.0217        | 11.0  | 77   | 0.2639          | 0.8571   |
| 0.0121        | 12.0  | 84   | 0.2977          | 0.8571   |
| 0.0105        | 13.0  | 91   | 0.3468          | 0.8571   |
| 0.0085        | 14.0  | 98   | 0.3912          | 0.8571   |
| 0.0077        | 15.0  | 105  | 0.4000          | 0.8571   |
| 0.0071        | 16.0  | 112  | 0.4015          | 0.8571   |
| 0.0078        | 17.0  | 119  | 0.3865          | 0.8571   |
| 0.0059        | 18.0  | 126  | 0.3603          | 0.8571   |
| 0.0051        | 19.0  | 133  | 0.3231          | 0.8571   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "distilbert-base-uncased__sst2__train-16-6", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased\_\_sst2\_\_train-16-6
=============================================


This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8356
* Accuracy: 0.6480


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: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* 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 4.15.0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* 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 4.15.0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* 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 4.15.0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* 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 4.15.0
* Pytorch 1.10.2+cu102
* Datasets 1.18.2
* Tokenizers 0.10.3