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# deberta-v3-base-squad2

This model is a fine-tuned version of [deepset/deberta-v3-base-squad2](https://huggingface.co/deepset/deberta-v3-base-squad2) on the subjqa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2514

## 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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.8874        | 1.0   | 81   | 3.4517          |
| 2.4367        | 2.0   | 162  | 3.0723          |
| 2.1531        | 3.0   | 243  | 2.8363          |
| 2.0393        | 4.0   | 324  | 2.6726          |
| 1.9166        | 5.0   | 405  | 2.5791          |
| 1.8508        | 6.0   | 486  | 2.4969          |
| 1.8035        | 7.0   | 567  | 2.4384          |
| 1.7348        | 8.0   | 648  | 2.3925          |
| 1.6939        | 9.0   | 729  | 2.3677          |
| 1.6754        | 10.0  | 810  | 2.3405          |
| 1.6283        | 11.0  | 891  | 2.2984          |
| 1.6159        | 12.0  | 972  | 2.2854          |
| 1.5893        | 13.0  | 1053 | 2.2793          |
| 1.5636        | 14.0  | 1134 | 2.2749          |
| 1.5779        | 15.0  | 1215 | 2.2629          |
| 1.567         | 16.0  | 1296 | 2.2563          |
| 1.5401        | 17.0  | 1377 | 2.2508          |
| 1.5494        | 18.0  | 1458 | 2.2514          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "datasets": ["subjqa"], "model-index": [{"name": "deberta-v3-base-squad2", "results": []}]}
transformers pytorch tensorboard deberta-v2 question-answering generated_from_trainer dataset:subjqa license:cc-by-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #question-answering #generated_from_trainer #dataset-subjqa #license-cc-by-4.0 #endpoints_compatible #region-us 

deberta-v3-base-squad2
======================


This model is a fine-tuned version of deepset/deberta-v3-base-squad2 on the subjqa dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2514


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: 1e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 18


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 18 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #question-answering #generated_from_trainer #dataset-subjqa #license-cc-by-4.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-06
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 18 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2