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# tBERT_big_AUD_USD_M15

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.8267
- Validation Loss: 4.1189
- Epoch: 20

## 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': 'AdamW', 'weight_decay': 0.004, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 0.0158     | 0.0710          | 0     |
| 0.0151     | 0.0729          | 1     |
| 0.0159     | 0.0729          | 2     |
| 2.3811     | 3.1534          | 3     |
| 2.7825     | 2.4722          | 4     |
| 2.2866     | 2.4094          | 5     |
| 2.2834     | 2.3846          | 6     |
| 2.0984     | 2.0451          | 7     |
| 2.0839     | 2.0866          | 8     |
| 2.1224     | 1.5450          | 9     |
| 1.9191     | 1.6559          | 10    |
| 1.8116     | 1.3405          | 11    |
| 1.4663     | 1.1409          | 12    |
| 1.1174     | 0.9641          | 13    |
| 0.9987     | 0.9052          | 14    |
| 1.9402     | 3.8288          | 15    |
| 3.8278     | 3.8280          | 16    |
| 3.8274     | 3.8277          | 17    |
| 3.8272     | 3.8295          | 18    |
| 3.8269     | 3.8295          | 19    |
| 3.8267     | 4.1189          | 20    |


### Framework versions

- Transformers 4.30.0.dev0
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "tBERT_big_AUD_USD_M15", "results": []}]}
transformers tf bert pretraining generated_from_keras_callback endpoints_compatible region:us
TAGS
#transformers #tf #bert #pretraining #generated_from_keras_callback #endpoints_compatible #region-us 

tBERT\_big\_AUD\_USD\_M15
=========================


This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:


* Train Loss: 3.8267
* Validation Loss: 4.1189
* Epoch: 20


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': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 5e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 5e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #bert #pretraining #generated_from_keras_callback #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 5e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #tf #bert #pretraining #generated_from_keras_callback #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'AdamW', 'weight\_decay': 0.004, 'clipnorm': None, 'global\_clipnorm': None, 'clipvalue': None, 'use\_ema': False, 'ema\_momentum': 0.99, 'ema\_overwrite\_frequency': None, 'jit\_compile': False, 'is\_legacy\_optimizer': False, 'learning\_rate': 5e-05, 'beta\_1': 0.9, 'beta\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
* training\_precision: float32### Training results### Framework versions


* Transformers 4.30.0.dev0
* TensorFlow 2.12.0
* Datasets 2.12.0
* Tokenizers 0.13.3