
<!-- 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. -->

# skillsBERT_v2_tf_epoch50

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: 0.0719
- Validation Loss: 6.8695
- Epoch: 49

## 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 |
|:----------:|:---------------:|:-----:|
| 6.9371     | 7.0394          | 0     |
| 6.2533     | 6.4021          | 1     |
| 5.3659     | 5.4458          | 2     |
| 4.6461     | 5.1474          | 3     |
| 4.1548     | 4.8846          | 4     |
| 3.7971     | 4.8365          | 5     |
| 3.4967     | 4.8230          | 6     |
| 3.2181     | 4.7250          | 7     |
| 2.9618     | 4.7563          | 8     |
| 2.7063     | 4.7626          | 9     |
| 2.4568     | 4.7971          | 10    |
| 2.2107     | 4.8674          | 11    |
| 1.9720     | 4.9420          | 12    |
| 1.7525     | 5.0023          | 13    |
| 1.5379     | 5.0225          | 14    |
| 1.3392     | 5.1210          | 15    |
| 1.1577     | 5.3786          | 16    |
| 0.9902     | 5.4268          | 17    |
| 0.8440     | 5.4760          | 18    |
| 0.7105     | 5.5502          | 19    |
| 0.5960     | 5.6959          | 20    |
| 0.4975     | 5.7828          | 21    |
| 0.4183     | 5.9094          | 22    |
| 0.3559     | 5.9433          | 23    |
| 0.3040     | 5.9871          | 24    |
| 0.2589     | 6.0707          | 25    |
| 0.2325     | 6.1771          | 26    |
| 0.2039     | 6.4244          | 27    |
| 0.1821     | 6.8064          | 28    |
| 0.1684     | 6.4322          | 29    |
| 0.1562     | 6.4103          | 30    |
| 0.1452     | 6.5123          | 31    |
| 0.1375     | 6.5841          | 32    |
| 0.1279     | 6.4424          | 33    |
| 0.1222     | 6.7928          | 34    |
| 0.1135     | 6.7001          | 35    |
| 0.1123     | 6.7584          | 36    |
| 0.1039     | 6.7425          | 37    |
| 0.1003     | 6.7665          | 38    |
| 0.0997     | 6.7972          | 39    |
| 0.0939     | 6.7379          | 40    |
| 0.0934     | 6.8585          | 41    |
| 0.0874     | 6.9250          | 42    |
| 0.0861     | 7.0405          | 43    |
| 0.0833     | 7.3141          | 44    |
| 0.0819     | 7.1149          | 45    |
| 0.0789     | 7.0914          | 46    |
| 0.0783     | 6.9386          | 47    |
| 0.0761     | 7.2007          | 48    |
| 0.0719     | 6.8695          | 49    |


### Framework versions

- Transformers 4.28.0.dev0
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "skillsBERT_v2_tf_epoch50", "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 

skillsBERT\_v2\_tf\_epoch50
===========================


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


* Train Loss: 0.0719
* Validation Loss: 6.8695
* Epoch: 49


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 4.28.0.dev0
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.2



### 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 4.28.0.dev0
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.2
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 4.28.0.dev0
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.2
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 4.28.0.dev0
* TensorFlow 2.12.0
* Datasets 2.11.0
* Tokenizers 0.13.2