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# hemagamal/mdeberta_quran_qa_model

This model is a fine-tuned version of [timpal0l/mdeberta-v3-base-squad2](https://huggingface.co/timpal0l/mdeberta-v3-base-squad2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 11.9013
- Train End Logits Loss: 5.9506
- Train Start Logits Loss: 5.9506
- Train End Logits Sparse Categorical Accuracy: 0.0582
- Train Start Logits Sparse Categorical Accuracy: 0.0426
- Validation Loss: 11.9013
- Validation End Logits Loss: 5.9506
- Validation Start Logits Loss: 5.9506
- Validation End Logits Sparse Categorical Accuracy: 0.0459
- Validation Start Logits Sparse Categorical Accuracy: 0.0917
- Epoch: 15

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train End Logits Loss | Train Start Logits Loss | Train End Logits Sparse Categorical Accuracy | Train Start Logits Sparse Categorical Accuracy | Validation Loss | Validation End Logits Loss | Validation Start Logits Loss | Validation End Logits Sparse Categorical Accuracy | Validation Start Logits Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------:|:-----------------------:|:--------------------------------------------:|:----------------------------------------------:|:---------------:|:--------------------------:|:----------------------------:|:-------------------------------------------------:|:---------------------------------------------------:|:-----:|
| 12.4236    | 6.1795                | 6.2441                  | 0.0724                                       | 0.0895                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 0     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0469                                       | 0.0469                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 1     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0369                                       | 0.0398                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 2     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0369                                       | 0.0554                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 3     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0483                                       | 0.0455                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 4     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0554                                       | 0.0412                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 5     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0241                                       | 0.0398                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 6     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0369                                       | 0.0412                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 7     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0426                                       | 0.0426                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 8     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0511                                       | 0.0426                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 9     |
| 11.9013    | 5.9506                | 5.9506                  | 0.0426                                       | 0.0469                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 10    |
| 11.9013    | 5.9506                | 5.9506                  | 0.0440                                       | 0.0341                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 11    |
| 11.9013    | 5.9506                | 5.9506                  | 0.0412                                       | 0.0398                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 12    |
| 11.9013    | 5.9506                | 5.9506                  | 0.0440                                       | 0.0440                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 13    |
| 11.9013    | 5.9506                | 5.9506                  | 0.0426                                       | 0.0412                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 14    |
| 11.9013    | 5.9506                | 5.9506                  | 0.0582                                       | 0.0426                                         | 11.9013         | 5.9506                     | 5.9506                       | 0.0459                                            | 0.0917                                              | 15    |


### Framework versions

- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "hemagamal/mdeberta_quran_qa_model", "results": []}]}
transformers tf deberta-v2 question-answering generated_from_keras_callback license:mit endpoints_compatible region:us
TAGS
#transformers #tf #deberta-v2 #question-answering #generated_from_keras_callback #license-mit #endpoints_compatible #region-us 

hemagamal/mdeberta\_quran\_qa\_model
====================================


This model is a fine-tuned version of timpal0l/mdeberta-v3-base-squad2 on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 11.9013
* Train End Logits Loss: 5.9506
* Train Start Logits Loss: 5.9506
* Train End Logits Sparse Categorical Accuracy: 0.0582
* Train Start Logits Sparse Categorical Accuracy: 0.0426
* Validation Loss: 11.9013
* Validation End Logits Loss: 5.9506
* Validation Start Logits Loss: 5.9506
* Validation End Logits Sparse Categorical Accuracy: 0.0459
* Validation Start Logits Sparse Categorical Accuracy: 0.0917
* Epoch: 15


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:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 2e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.29.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 2e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #deberta-v2 #question-answering #generated_from_keras_callback #license-mit #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'weight\_decay': None, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': True, 'is\_legacy\_optimizer': False, 'learning\_rate': 2e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3