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# mallikrao2/qa-finetuned-swag

This model is a fine-tuned version of [mallikrao2/sQuad_bertmodel1_](https://huggingface.co/mallikrao2/sQuad_bertmodel1_) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0020
- Train Accuracy: 0.9994
- Validation Loss: 1.9750
- Validation Accuracy: 0.7508
- Epoch: 19

## 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 66860, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.8405     | 0.6630         | 0.6156          | 0.7596              | 0     |
| 0.4697     | 0.8233         | 0.6102          | 0.7643              | 1     |
| 0.2479     | 0.9087         | 0.7102          | 0.7573              | 2     |
| 0.1571     | 0.9439         | 0.8434          | 0.7482              | 3     |
| 0.1139     | 0.9599         | 1.0923          | 0.7453              | 4     |
| 0.0881     | 0.9698         | 1.0614          | 0.7421              | 5     |
| 0.0705     | 0.9758         | 1.1311          | 0.7412              | 6     |
| 0.0577     | 0.9802         | 1.1761          | 0.7387              | 7     |
| 0.0453     | 0.9845         | 1.3310          | 0.7446              | 8     |
| 0.0379     | 0.9869         | 1.3076          | 0.7361              | 9     |
| 0.0301     | 0.9898         | 1.3147          | 0.7434              | 10    |
| 0.0228     | 0.9923         | 1.6641          | 0.7388              | 11    |
| 0.0195     | 0.9932         | 1.6168          | 0.7397              | 12    |
| 0.0165     | 0.9948         | 1.6042          | 0.7458              | 13    |
| 0.0118     | 0.9960         | 1.6922          | 0.7426              | 14    |
| 0.0098     | 0.9970         | 1.7052          | 0.7449              | 15    |
| 0.0059     | 0.9982         | 1.8137          | 0.7453              | 16    |
| 0.0040     | 0.9986         | 1.9369          | 0.7504              | 17    |
| 0.0032     | 0.9991         | 1.9089          | 0.7498              | 18    |
| 0.0020     | 0.9994         | 1.9750          | 0.7508              | 19    |


### Framework versions

- Transformers 4.29.2
- TensorFlow 2.8.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "mallikrao2/qa-finetuned-swag", "results": []}]}
transformers tf tensorboard bert multiple-choice generated_from_keras_callback license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #bert #multiple-choice #generated_from_keras_callback #license-apache-2.0 #endpoints_compatible #region-us 

mallikrao2/qa-finetuned-swag
============================


This model is a fine-tuned version of mallikrao2/sQuad\_bertmodel1\_ on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 0.0020
* Train Accuracy: 0.9994
* Validation Loss: 1.9750
* Validation Accuracy: 0.7508
* Epoch: 19


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', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 66860, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.29.2
* TensorFlow 2.8.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 66860, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.8.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #tensorboard #bert #multiple-choice #generated_from_keras_callback #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 5e-05, 'decay\_steps': 66860, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.29.2
* TensorFlow 2.8.0
* Datasets 2.12.0
* Tokenizers 0.13.3