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# deberta_squadnewsqa

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the Squad_v2 and NewsQA datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9648

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.0355        | 1.0   | 14875 | 0.9648          |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3
{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad_v2", "newsqa"], "model-index": [{"name": "deberta_squadnewsqa", "results": []}]}
transformers pytorch deberta-v2 question-answering generated_from_trainer dataset:squad_v2 dataset:newsqa license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #question-answering #generated_from_trainer #dataset-squad_v2 #dataset-newsqa #license-mit #endpoints_compatible #region-us 

deberta\_squadnewsqa
====================


This model is a fine-tuned version of microsoft/deberta-v3-base on the Squad\_v2 and NewsQA datasets.
It achieves the following results on the evaluation set:


* Loss: 0.9648


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #deberta-v2 #question-answering #generated_from_trainer #dataset-squad_v2 #dataset-newsqa #license-mit #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3