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# Andronius17/answer_text

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.9377
- Validation Loss: 3.9762
- Epoch: 32

## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 84, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.1663     | 3.9762          | 0     |
| 3.9427     | 3.9762          | 1     |
| 3.9499     | 3.9762          | 2     |
| 3.9448     | 3.9762          | 3     |
| 3.9429     | 3.9762          | 4     |
| 3.9460     | 3.9762          | 5     |
| 3.9372     | 3.9762          | 6     |
| 3.9375     | 3.9762          | 7     |
| 3.9359     | 3.9762          | 8     |
| 3.9398     | 3.9762          | 9     |
| 3.9488     | 3.9762          | 10    |
| 3.9429     | 3.9762          | 11    |
| 3.9482     | 3.9762          | 12    |
| 3.9383     | 3.9762          | 13    |
| 3.9415     | 3.9762          | 14    |
| 3.9377     | 3.9762          | 15    |
| 3.9440     | 3.9762          | 16    |
| 3.9415     | 3.9762          | 17    |
| 3.9374     | 3.9762          | 18    |
| 3.9327     | 3.9762          | 19    |
| 3.9477     | 3.9762          | 20    |
| 3.9424     | 3.9762          | 21    |
| 3.9375     | 3.9762          | 22    |
| 3.9419     | 3.9762          | 23    |
| 3.9459     | 3.9762          | 24    |
| 3.9463     | 3.9762          | 25    |
| 3.9410     | 3.9762          | 26    |
| 3.9414     | 3.9762          | 27    |
| 3.9458     | 3.9762          | 28    |
| 3.9479     | 3.9762          | 29    |
| 3.9370     | 3.9762          | 30    |
| 3.9465     | 3.9762          | 31    |
| 3.9377     | 3.9762          | 32    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Andronius17/answer_text", "results": []}]}
transformers tf distilbert question-answering generated_from_keras_callback license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #tf #distilbert #question-answering #generated_from_keras_callback #license-apache-2.0 #endpoints_compatible #region-us 

Andronius17/answer\_text
========================


This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 3.9377
* Validation Loss: 3.9762
* Epoch: 32


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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 84, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* 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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 84, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #distilbert #question-answering #generated_from_keras_callback #license-apache-2.0 #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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 84, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #distilbert #question-answering #generated_from_keras_callback #license-apache-2.0 #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': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 2e-05, 'decay\_steps': 84, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.3