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# skillsBERT_v2_tf_epoch200

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: 0.0276
- Validation Loss: 8.4065
- Epoch: 199

## 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 |
|:----------:|:---------------:|:-----:|
| 6.9368     | 6.9678          | 0     |
| 6.1821     | 6.1973          | 1     |
| 5.2896     | 5.5216          | 2     |
| 4.6036     | 5.0930          | 3     |
| 4.1260     | 4.9491          | 4     |
| 3.7779     | 4.7258          | 5     |
| 3.4894     | 4.7463          | 6     |
| 3.2243     | 4.6753          | 7     |
| 2.9684     | 4.7601          | 8     |
| 2.7213     | 4.7217          | 9     |
| 2.4751     | 4.7763          | 10    |
| 2.2359     | 4.9020          | 11    |
| 1.9973     | 4.9020          | 12    |
| 1.7702     | 5.1024          | 13    |
| 1.5533     | 5.0703          | 14    |
| 1.3533     | 5.2204          | 15    |
| 1.1692     | 5.3927          | 16    |
| 1.0013     | 5.3786          | 17    |
| 0.8445     | 5.5459          | 18    |
| 0.7170     | 5.5764          | 19    |
| 0.5973     | 5.6444          | 20    |
| 0.5046     | 5.8587          | 21    |
| 0.4235     | 5.8703          | 22    |
| 0.3569     | 5.8058          | 23    |
| 0.3052     | 6.1211          | 24    |
| 0.2655     | 5.9994          | 25    |
| 0.2298     | 6.4393          | 26    |
| 0.2044     | 6.3036          | 27    |
| 0.1878     | 6.3250          | 28    |
| 0.1713     | 6.3984          | 29    |
| 0.1566     | 6.3334          | 30    |
| 0.1463     | 6.6641          | 31    |
| 0.1359     | 6.5607          | 32    |
| 0.1298     | 6.8457          | 33    |
| 0.1216     | 6.5984          | 34    |
| 0.1176     | 6.6329          | 35    |
| 0.1112     | 7.0239          | 36    |
| 0.1071     | 6.6365          | 37    |
| 0.1010     | 6.7788          | 38    |
| 0.0976     | 6.9059          | 39    |
| 0.0971     | 7.0272          | 40    |
| 0.0954     | 6.9061          | 41    |
| 0.0907     | 6.7402          | 42    |
| 0.0849     | 6.8301          | 43    |
| 0.0826     | 7.0355          | 44    |
| 0.0858     | 6.9938          | 45    |
| 0.0809     | 7.0757          | 46    |
| 0.0783     | 7.1545          | 47    |
| 0.0744     | 7.3133          | 48    |
| 0.0716     | 7.2899          | 49    |
| 0.0750     | 7.4284          | 50    |
| 0.0722     | 7.3191          | 51    |
| 0.0723     | 7.2923          | 52    |
| 0.0666     | 7.3033          | 53    |
| 0.0710     | 7.2679          | 54    |
| 0.0650     | 7.2664          | 55    |
| 0.0661     | 7.1938          | 56    |
| 0.0640     | 7.1925          | 57    |
| 0.0641     | 7.4666          | 58    |
| 0.0602     | 7.3531          | 59    |
| 0.0625     | 7.2725          | 60    |
| 0.0627     | 7.4885          | 61    |
| 0.0620     | 7.3922          | 62    |
| 0.0552     | 7.4525          | 63    |
| 0.0594     | 7.2247          | 64    |
| 0.0581     | 7.3419          | 65    |
| 0.0548     | 7.4633          | 66    |
| 0.0583     | 7.5051          | 67    |
| 0.0543     | 7.3567          | 68    |
| 0.0545     | 7.4085          | 69    |
| 0.0539     | 7.5690          | 70    |
| 0.0546     | 7.3862          | 71    |
| 0.0511     | 7.7210          | 72    |
| 0.0530     | 7.5558          | 73    |
| 0.0516     | 7.8195          | 74    |
| 0.0501     | 7.5061          | 75    |
| 0.0521     | 7.5066          | 76    |
| 0.0499     | 7.6577          | 77    |
| 0.0501     | 7.5698          | 78    |
| 0.0497     | 7.5531          | 79    |
| 0.0480     | 7.3663          | 80    |
| 0.0482     | 7.5768          | 81    |
| 0.0487     | 7.5996          | 82    |
| 0.0487     | 7.3785          | 83    |
| 0.0472     | 7.6577          | 84    |
| 0.0457     | 7.5219          | 85    |
| 0.0465     | 7.6445          | 86    |
| 0.0465     | 7.4914          | 87    |
| 0.0466     | 7.7647          | 88    |
| 0.0451     | 7.6801          | 89    |
| 0.0443     | 7.7295          | 90    |
| 0.0461     | 7.7421          | 91    |
| 0.0454     | 7.7623          | 92    |
| 0.0442     | 7.6821          | 93    |
| 0.0430     | 7.9835          | 94    |
| 0.0449     | 7.6681          | 95    |
| 0.0430     | 7.8815          | 96    |
| 0.0424     | 7.9022          | 97    |
| 0.0445     | 7.8707          | 98    |
| 0.0431     | 7.7530          | 99    |
| 0.0421     | 7.7138          | 100   |
| 0.0414     | 7.7932          | 101   |
| 0.0425     | 7.5632          | 102   |
| 0.0379     | 7.8132          | 103   |
| 0.0433     | 7.6901          | 104   |
| 0.0386     | 7.8083          | 105   |
| 0.0426     | 7.7248          | 106   |
| 0.0410     | 7.8584          | 107   |
| 0.0418     | 7.7491          | 108   |
| 0.0401     | 7.8016          | 109   |
| 0.0421     | 7.7656          | 110   |
| 0.0389     | 7.8427          | 111   |
| 0.0389     | 7.7864          | 112   |
| 0.0396     | 7.8669          | 113   |
| 0.0396     | 7.7623          | 114   |
| 0.0379     | 7.8776          | 115   |
| 0.0392     | 7.9052          | 116   |
| 0.0390     | 7.8197          | 117   |
| 0.0406     | 7.8233          | 118   |
| 0.0371     | 7.8755          | 119   |
| 0.0395     | 7.9325          | 120   |
| 0.0369     | 8.0833          | 121   |
| 0.0373     | 7.9204          | 122   |
| 0.0372     | 8.0792          | 123   |
| 0.0391     | 7.7565          | 124   |
| 0.0347     | 7.8271          | 125   |
| 0.0373     | 7.9994          | 126   |
| 0.0365     | 8.0182          | 127   |
| 0.0362     | 8.1003          | 128   |
| 0.0371     | 8.0342          | 129   |
| 0.0362     | 8.1524          | 130   |
| 0.0374     | 8.0588          | 131   |
| 0.0355     | 7.9384          | 132   |
| 0.0349     | 8.0925          | 133   |
| 0.0358     | 8.1963          | 134   |
| 0.0367     | 7.9769          | 135   |
| 0.0347     | 7.8656          | 136   |
| 0.0349     | 8.0004          | 137   |
| 0.0339     | 7.9382          | 138   |
| 0.0371     | 8.1195          | 139   |
| 0.0360     | 7.9568          | 140   |
| 0.0308     | 8.0514          | 141   |
| 0.0370     | 7.8408          | 142   |
| 0.0344     | 7.9932          | 143   |
| 0.0328     | 8.0507          | 144   |
| 0.0323     | 8.1716          | 145   |
| 0.0347     | 7.9123          | 146   |
| 0.0330     | 8.0947          | 147   |
| 0.0347     | 7.9371          | 148   |
| 0.0357     | 8.1293          | 149   |
| 0.0318     | 8.1566          | 150   |
| 0.0352     | 8.1061          | 151   |
| 0.0320     | 8.4313          | 152   |
| 0.0339     | 8.0567          | 153   |
| 0.0318     | 8.1668          | 154   |
| 0.0352     | 7.8946          | 155   |
| 0.0327     | 8.0129          | 156   |
| 0.0336     | 8.2448          | 157   |
| 0.0328     | 7.9567          | 158   |
| 0.0339     | 7.9868          | 159   |
| 0.0320     | 7.9006          | 160   |
| 0.0321     | 8.3043          | 161   |
| 0.0324     | 8.0456          | 162   |
| 0.0327     | 8.0358          | 163   |
| 0.0304     | 8.1395          | 164   |
| 0.0315     | 8.1250          | 165   |
| 0.0338     | 8.1198          | 166   |
| 0.0345     | 8.0466          | 167   |
| 0.0304     | 8.0713          | 168   |
| 0.0277     | 8.0176          | 169   |
| 0.0334     | 8.2149          | 170   |
| 0.0292     | 8.2865          | 171   |
| 0.0315     | 8.1717          | 172   |
| 0.0313     | 8.3362          | 173   |
| 0.0324     | 8.1874          | 174   |
| 0.0312     | 8.1653          | 175   |
| 0.0319     | 8.1341          | 176   |
| 0.0297     | 8.1978          | 177   |
| 0.0321     | 8.1678          | 178   |
| 0.0326     | 8.2196          | 179   |
| 0.0294     | 8.1050          | 180   |
| 0.0300     | 8.0882          | 181   |
| 0.0305     | 8.2307          | 182   |
| 0.0304     | 8.2959          | 183   |
| 0.0300     | 8.2581          | 184   |
| 0.0288     | 8.1481          | 185   |
| 0.0305     | 8.2346          | 186   |
| 0.0306     | 8.1175          | 187   |
| 0.0311     | 8.2394          | 188   |
| 0.0298     | 8.1912          | 189   |
| 0.0277     | 8.2177          | 190   |
| 0.0315     | 8.1094          | 191   |
| 0.0305     | 8.1813          | 192   |
| 0.0283     | 8.3636          | 193   |
| 0.0307     | 8.3034          | 194   |
| 0.0280     | 8.3165          | 195   |
| 0.0309     | 8.3315          | 196   |
| 0.0275     | 8.3439          | 197   |
| 0.0314     | 8.3021          | 198   |
| 0.0276     | 8.4065          | 199   |


### 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_epoch200", "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\_epoch200
============================


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


* Train Loss: 0.0276
* Validation Loss: 8.4065
* Epoch: 199


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