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# GCopoulos/deberta-base-finetuned-answer_pol

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0755
- Validation Loss: 0.6949
- Train F1: 0.8489
- Epoch: 2

## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 7e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 7e-05, 'decay_steps': 653, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 10, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train F1 | Epoch |
|:----------:|:---------------:|:--------:|:-----:|
| 0.5343     | 0.6051          | 0.8389   | 0     |
| 0.1790     | 0.7237          | 0.8194   | 1     |
| 0.0755     | 0.6949          | 0.8489   | 2     |


### Framework versions

- Transformers 4.30.0
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "GCopoulos/deberta-base-finetuned-answer_pol", "results": []}]}
transformers tf tensorboard deberta text-classification generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #tensorboard #deberta #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 

GCopoulos/deberta-base-finetuned-answer\_pol
============================================


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


* Train Loss: 0.0755
* Validation Loss: 0.6949
* Train F1: 0.8489
* Epoch: 2


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': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_steps': 653, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 10, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.30.0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_steps': 653, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 10, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #tensorboard #deberta #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamWeightDecay', 'learning\_rate': {'class\_name': 'WarmUp', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_schedule\_fn': {'class\_name': 'PolynomialDecay', 'config': {'initial\_learning\_rate': 7e-05, 'decay\_steps': 653, 'end\_learning\_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '**passive\_serialization**': True}, 'warmup\_steps': 10, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight\_decay\_rate': 0.01}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3