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# Regression_roberta_1

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3891
- Train Mae: 0.3117
- Train Mse: 0.1477
- Train R2-score: 0.7113
- Train Accuracy: 0.7077
- Validation Loss: 0.3272
- Validation Mae: 0.3256
- Validation Mse: 0.1253
- Validation R2-score: 0.8839
- Validation Accuracy: 0.9459
- Epoch: 9

## 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 Mae | Train Mse | Train R2-score | Train Accuracy | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Validation Accuracy | Epoch |
|:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:|
| 0.4486     | 0.2939    | 0.1319    | 0.7250         | 0.7769         | 0.4177          | 0.4165         | 0.2221         | 0.8321              | 0.3243              | 0     |
| 0.3684     | 0.2898    | 0.1342    | 0.5541         | 0.7462         | 0.4019          | 0.4006         | 0.2091         | 0.8409              | 0.3243              | 1     |
| 0.3423     | 0.2854    | 0.1299    | 0.7355         | 0.7462         | 0.3971          | 0.3958         | 0.2050         | 0.8438              | 0.3243              | 2     |
| 0.3514     | 0.2890    | 0.1324    | 0.7935         | 0.7538         | 0.3552          | 0.3538         | 0.1640         | 0.8681              | 0.9459              | 3     |
| 0.3722     | 0.3107    | 0.1525    | 0.5604         | 0.7000         | 0.3448          | 0.3432         | 0.1484         | 0.8750              | 0.9459              | 4     |
| 0.3996     | 0.2949    | 0.1305    | 0.7869         | 0.8231         | 0.3692          | 0.3677         | 0.1794         | 0.8514              | 0.4865              | 5     |
| 0.3441     | 0.2895    | 0.1322    | 0.7546         | 0.7538         | 0.3186          | 0.3169         | 0.1159         | 0.8860              | 0.9459              | 6     |
| 0.3898     | 0.2921    | 0.1255    | 0.5919         | 0.7692         | 0.4107          | 0.4095         | 0.2160         | 0.8366              | 0.3243              | 7     |
| 0.3552     | 0.2868    | 0.1297    | 0.7113         | 0.7538         | 0.4426          | 0.4415         | 0.2434         | 0.8179              | 0.3243              | 8     |
| 0.3891     | 0.3117    | 0.1477    | 0.7113         | 0.7077         | 0.3272          | 0.3256         | 0.1253         | 0.8839              | 0.9459              | 9     |


### Framework versions

- Transformers 4.27.2
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Regression_roberta_1", "results": []}]}
transformers tf roberta text-classification generated_from_keras_callback license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #roberta #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us 

Regression\_roberta\_1
======================


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


* Train Loss: 0.3891
* Train Mae: 0.3117
* Train Mse: 0.1477
* Train R2-score: 0.7113
* Train Accuracy: 0.7077
* Validation Loss: 0.3272
* Validation Mae: 0.3256
* Validation Mse: 0.1253
* Validation R2-score: 0.8839
* Validation Accuracy: 0.9459
* Epoch: 9


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 4.27.2
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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 4.27.2
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #roberta #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': '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 4.27.2
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #tf #roberta #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': '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 4.27.2
* TensorFlow 2.11.0
* Datasets 2.10.1
* Tokenizers 0.13.2