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# pretrained-m-bert-90

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: 5.7094
- Validation Loss: 14.5332
- Epoch: 89

## 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 | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 10.2413    | 10.9668         | 0     |
| 7.5814     | 10.9638         | 1     |
| 7.0095     | 11.3733         | 2     |
| 6.4352     | 11.5989         | 3     |
| 6.7137     | 11.4072         | 4     |
| 6.4383     | 11.8287         | 5     |
| 6.2223     | 12.0344         | 6     |
| 6.1759     | 11.6900         | 7     |
| 6.0764     | 11.7144         | 8     |
| 5.8802     | 12.1089         | 9     |
| 6.0159     | 12.3456         | 10    |
| 5.9254     | 12.7065         | 11    |
| 5.6652     | nan             | 12    |
| 5.8185     | 12.8155         | 13    |
| 5.9185     | 12.7047         | 14    |
| 5.8418     | 12.7175         | 15    |
| 5.9122     | 12.5688         | 16    |
| 5.9698     | 12.5251         | 17    |
| 5.8286     | 12.7015         | 18    |
| 5.8807     | 13.2514         | 19    |
| 5.8330     | 12.8541         | 20    |
| 5.6456     | 13.4088         | 21    |
| 5.7257     | 13.5517         | 22    |
| 5.8854     | 12.8775         | 23    |
| 5.6770     | 13.6499         | 24    |
| 5.6026     | 13.9732         | 25    |
| 5.6651     | 13.0827         | 26    |
| 5.8888     | 13.1292         | 27    |
| 5.8123     | 12.8970         | 28    |
| 5.7525     | 13.3724         | 29    |
| 5.9020     | 13.5507         | 30    |
| 5.8642     | 13.3284         | 31    |
| 5.9329     | 13.7350         | 32    |
| 5.7728     | 13.3011         | 33    |
| 5.8297     | 13.6108         | 34    |
| 5.8118     | 13.3331         | 35    |
| 5.7382     | 13.7047         | 36    |
| 5.8061     | 13.8107         | 37    |
| 5.8423     | 13.4207         | 38    |
| 5.8442     | 13.6832         | 39    |
| 5.7680     | 14.1248         | 40    |
| 5.7668     | 13.6626         | 41    |
| 5.7826     | 13.6470         | 42    |
| 5.7692     | 13.9430         | 43    |
| 5.5109     | 14.0924         | 44    |
| 5.7394     | 14.0253         | 45    |
| 5.8013     | 13.5926         | 46    |
| 5.7222     | 13.9732         | 47    |
| 5.7023     | 14.0204         | 48    |
| 5.8250     | 13.9655         | 49    |
| 5.6064     | 14.0406         | 50    |
| 5.7319     | 14.1826         | 51    |
| 5.6849     | 13.9114         | 52    |
| 5.8167     | 13.9917         | 53    |
| 5.7573     | 14.1509         | 54    |
| 5.6921     | 14.3722         | 55    |
| 5.7190     | 14.4919         | 56    |
| 5.8501     | 13.6970         | 57    |
| 5.7627     | 14.1393         | 58    |
| 5.8031     | 14.1246         | 59    |
| 5.7207     | 14.3084         | 60    |
| 5.7979     | 13.9398         | 61    |
| 5.7068     | 14.2865         | 62    |
| 5.7547     | 14.2590         | 63    |
| 5.8349     | 14.1481         | 64    |
| 5.7924     | 14.0461         | 65    |
| 5.8127     | 14.1274         | 66    |
| 5.7590     | 14.3578         | 67    |
| 5.8297     | 14.2429         | 68    |
| 5.7822     | 14.2742         | 69    |
| 5.7708     | 14.3720         | 70    |
| 5.6521     | 14.8640         | 71    |
| 5.7253     | 14.4404         | 72    |
| 5.8076     | 14.1843         | 73    |
| 5.7746     | 14.4657         | 74    |
| 5.8592     | 14.2965         | 75    |
| 5.6643     | 14.0996         | 76    |
| 5.7849     | 14.3531         | 77    |
| 5.7418     | 14.4266         | 78    |
| 5.7030     | 14.5584         | 79    |
| 5.8298     | 14.1390         | 80    |
| 5.9061     | 13.9172         | 81    |
| 5.6570     | 14.6991         | 82    |
| 5.7040     | 14.7839         | 83    |
| 5.8064     | 14.2581         | 84    |
| 5.6855     | 14.4449         | 85    |
| 5.7803     | 14.7469         | 86    |
| 5.7495     | 14.4704         | 87    |
| 5.7539     | 14.5520         | 88    |
| 5.7094     | 14.5332         | 89    |


### Framework versions

- Transformers 4.27.0.dev0
- TensorFlow 2.11.0
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "pretrained-m-bert-90", "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 

pretrained-m-bert-90
====================


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


* Train Loss: 5.7094
* Validation Loss: 14.5332
* Epoch: 89


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 4.27.0.dev0
* TensorFlow 2.11.0
* Datasets 2.9.0
* Tokenizers 0.13.2



### 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 4.27.0.dev0
* TensorFlow 2.11.0
* Datasets 2.9.0
* 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': '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 4.27.0.dev0
* TensorFlow 2.11.0
* Datasets 2.9.0
* 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': '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 4.27.0.dev0
* TensorFlow 2.11.0
* Datasets 2.9.0
* Tokenizers 0.13.2