
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Regression_bert_aug_CustomLoss_2

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: 0.2338
- Train Mae: 0.5263
- Train Mse: 0.4258
- Train R2-score: 0.7899
- Validation Loss: 0.2340
- Validation Mae: 0.5490
- Validation Mse: 0.4329
- Validation R2-score: 0.7254
- Epoch: 14

## 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': 1e-04, '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 | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Epoch |
|:----------:|:---------:|:---------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-----:|
| 0.2004     | 0.4982    | 0.3687    | 0.6907         | 0.1488          | 0.4239         | 0.3023         | 0.7428              | 0     |
| 0.1118     | 0.4054    | 0.2460    | 0.7552         | 0.0783          | 0.3502         | 0.1873         | 0.8501              | 1     |
| 0.0531     | 0.3256    | 0.1543    | 0.8049         | 0.0489          | 0.3257         | 0.1489         | 0.8412              | 2     |
| 0.0342     | 0.2826    | 0.1151    | 0.7986         | 0.0328          | 0.2697         | 0.1215         | 0.9246              | 3     |
| 0.0266     | 0.2587    | 0.0962    | 0.8802         | 0.0713          | 0.2884         | 0.1297         | 0.8729              | 4     |
| 0.0543     | 0.3022    | 0.1388    | 0.7724         | 0.0609          | 0.3238         | 0.1524         | 0.7723              | 5     |
| 0.0380     | 0.2756    | 0.1114    | 0.8822         | 0.0421          | 0.1984         | 0.0700         | 0.9070              | 6     |
| 0.0593     | 0.3134    | 0.1537    | 0.8764         | 0.2335          | 0.5183         | 0.4636         | 0.7816              | 7     |
| 0.2330     | 0.5234    | 0.4182    | -1.5020        | 0.2656          | 0.5726         | 0.3948         | 0.5533              | 8     |
| 0.2359     | 0.5149    | 0.4195    | 0.7932         | 0.2347          | 0.5263         | 0.4461         | 0.7502              | 9     |
| 0.2341     | 0.5204    | 0.4268    | 0.8100         | 0.2341          | 0.5509         | 0.4307         | 0.7220              | 10    |
| 0.2335     | 0.5250    | 0.4235    | 0.8053         | 0.2328          | 0.5433         | 0.4334         | 0.7322              | 11    |
| 0.2319     | 0.5217    | 0.4244    | 0.7825         | 0.2352          | 0.5549         | 0.4296         | 0.7158              | 12    |
| 0.2323     | 0.5243    | 0.4234    | 0.7877         | 0.2346          | 0.5536         | 0.4286         | 0.7170              | 13    |
| 0.2338     | 0.5263    | 0.4258    | 0.7899         | 0.2340          | 0.5490         | 0.4329         | 0.7254              | 14    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Regression_bert_aug_CustomLoss_2", "results": []}]}
transformers tf distilbert text-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Regression\_bert\_aug\_CustomLoss\_2
====================================


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: 0.2338
* Train Mae: 0.5263
* Train Mse: 0.4258
* Train R2-score: 0.7899
* Validation Loss: 0.2340
* Validation Mae: 0.5490
* Validation Mse: 0.4329
* Validation R2-score: 0.7254
* Epoch: 14


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': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.28.1
* 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': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.28.1
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #distilbert #text-classification #generated_from_keras_callback #license-apache-2.0 #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': 1e-04, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


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