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# skillsBERT_v2_tf_epoch100

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: 0.0434
- Validation Loss: 7.6168
- Epoch: 99

## 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 |
|:----------:|:---------------:|:-----:|
| 6.9352     | 6.9523          | 0     |
| 6.2407     | 6.4961          | 1     |
| 5.3385     | 5.4546          | 2     |
| 4.5980     | 5.2382          | 3     |
| 4.1083     | 4.9088          | 4     |
| 3.7477     | 4.7707          | 5     |
| 3.4448     | 4.7855          | 6     |
| 3.1698     | 4.8487          | 7     |
| 2.9094     | 4.6565          | 8     |
| 2.6538     | 4.7127          | 9     |
| 2.4067     | 4.7005          | 10    |
| 2.1610     | 4.7585          | 11    |
| 1.9259     | 4.9684          | 12    |
| 1.6975     | 5.1386          | 13    |
| 1.4856     | 5.1549          | 14    |
| 1.2886     | 5.1025          | 15    |
| 1.1029     | 5.1759          | 16    |
| 0.9386     | 5.4045          | 17    |
| 0.7907     | 5.6535          | 18    |
| 0.6633     | 5.6907          | 19    |
| 0.5530     | 5.7347          | 20    |
| 0.4623     | 5.7088          | 21    |
| 0.3864     | 5.7850          | 22    |
| 0.3280     | 5.8012          | 23    |
| 0.2797     | 6.1019          | 24    |
| 0.2434     | 6.1027          | 25    |
| 0.2097     | 6.3630          | 26    |
| 0.1895     | 6.2085          | 27    |
| 0.1734     | 6.2182          | 28    |
| 0.1578     | 6.3494          | 29    |
| 0.1444     | 6.3452          | 30    |
| 0.1354     | 6.7442          | 31    |
| 0.1313     | 6.5799          | 32    |
| 0.1172     | 6.7019          | 33    |
| 0.1178     | 6.5615          | 34    |
| 0.1115     | 6.6848          | 35    |
| 0.1070     | 6.7984          | 36    |
| 0.1000     | 6.8200          | 37    |
| 0.0998     | 6.9078          | 38    |
| 0.0922     | 6.8531          | 39    |
| 0.0890     | 7.0363          | 40    |
| 0.0880     | 6.9250          | 41    |
| 0.0852     | 7.1117          | 42    |
| 0.0841     | 6.8522          | 43    |
| 0.0818     | 6.9779          | 44    |
| 0.0785     | 7.0038          | 45    |
| 0.0779     | 6.9143          | 46    |
| 0.0731     | 7.0954          | 47    |
| 0.0734     | 7.3798          | 48    |
| 0.0706     | 7.2156          | 49    |
| 0.0713     | 7.0388          | 50    |
| 0.0699     | 7.0339          | 51    |
| 0.0667     | 7.1569          | 52    |
| 0.0664     | 7.3617          | 53    |
| 0.0647     | 7.2491          | 54    |
| 0.0647     | 7.2064          | 55    |
| 0.0658     | 7.3093          | 56    |
| 0.0612     | 7.2296          | 57    |
| 0.0602     | 7.2176          | 58    |
| 0.0613     | 7.3468          | 59    |
| 0.0587     | 7.3203          | 60    |
| 0.0584     | 7.5229          | 61    |
| 0.0571     | 7.4048          | 62    |
| 0.0585     | 7.2250          | 63    |
| 0.0575     | 7.1258          | 64    |
| 0.0548     | 7.3677          | 65    |
| 0.0556     | 7.6926          | 66    |
| 0.0545     | 7.3272          | 67    |
| 0.0542     | 7.5853          | 68    |
| 0.0545     | 7.5508          | 69    |
| 0.0525     | 7.4420          | 70    |
| 0.0526     | 7.3759          | 71    |
| 0.0515     | 7.3879          | 72    |
| 0.0502     | 7.4672          | 73    |
| 0.0532     | 7.2759          | 74    |
| 0.0493     | 7.6825          | 75    |
| 0.0469     | 7.8799          | 76    |
| 0.0463     | 7.5466          | 77    |
| 0.0480     | 7.5932          | 78    |
| 0.0505     | 7.5632          | 79    |
| 0.0477     | 7.7247          | 80    |
| 0.0474     | 7.4508          | 81    |
| 0.0464     | 7.5723          | 82    |
| 0.0461     | 7.5043          | 83    |
| 0.0470     | 7.6296          | 84    |
| 0.0455     | 7.6214          | 85    |
| 0.0479     | 7.4556          | 86    |
| 0.0444     | 7.3914          | 87    |
| 0.0445     | 7.6954          | 88    |
| 0.0457     | 7.6601          | 89    |
| 0.0453     | 7.4933          | 90    |
| 0.0443     | 7.7381          | 91    |
| 0.0429     | 7.6079          | 92    |
| 0.0413     | 7.7611          | 93    |
| 0.0451     | 7.8315          | 94    |
| 0.0397     | 7.7161          | 95    |
| 0.0450     | 7.9785          | 96    |
| 0.0386     | 7.7460          | 97    |
| 0.0434     | 7.7243          | 98    |
| 0.0434     | 7.6168          | 99    |


### 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_epoch100", "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\_epoch100
============================


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


* Train Loss: 0.0434
* Validation Loss: 7.6168
* Epoch: 99


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