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# deberta-v3-large__sst2__train-16-5

This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5433
- Accuracy: 0.7924

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6774        | 1.0   | 7    | 0.7450          | 0.2857   |
| 0.7017        | 2.0   | 14   | 0.7552          | 0.2857   |
| 0.6438        | 3.0   | 21   | 0.7140          | 0.4286   |
| 0.3525        | 4.0   | 28   | 0.5570          | 0.7143   |
| 0.2061        | 5.0   | 35   | 0.5303          | 0.8571   |
| 0.0205        | 6.0   | 42   | 0.6706          | 0.8571   |
| 0.0068        | 7.0   | 49   | 0.8284          | 0.8571   |
| 0.0029        | 8.0   | 56   | 0.9281          | 0.8571   |
| 0.0015        | 9.0   | 63   | 0.9871          | 0.8571   |
| 0.0013        | 10.0  | 70   | 1.0208          | 0.8571   |
| 0.0008        | 11.0  | 77   | 1.0329          | 0.8571   |
| 0.0005        | 12.0  | 84   | 1.0348          | 0.8571   |
| 0.0004        | 13.0  | 91   | 1.0437          | 0.8571   |
| 0.0005        | 14.0  | 98   | 1.0512          | 0.8571   |
| 0.0004        | 15.0  | 105  | 1.0639          | 0.8571   |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/deberta-v3-large", "model-index": [{"name": "deberta-v3-large__sst2__train-16-5", "results": []}]}
transformers pytorch deberta-v2 text-classification generated_from_trainer base_model:microsoft/deberta-v3-large license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #text-classification #generated_from_trainer #base_model-microsoft/deberta-v3-large #license-mit #autotrain_compatible #endpoints_compatible #region-us 

deberta-v3-large\_\_sst2\_\_train-16-5
======================================


This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5433
* Accuracy: 0.7924


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 #deberta-v2 #text-classification #generated_from_trainer #base_model-microsoft/deberta-v3-large #license-mit #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 #deberta-v2 #text-classification #generated_from_trainer #base_model-microsoft/deberta-v3-large #license-mit #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