
<!-- 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. -->

# pretrained-bert-base-100

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: 5.5798
- Validation Loss: 14.1522
- 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': '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 |
|:----------:|:---------------:|:-----:|
| 8.8180     | 9.8287          | 0     |
| 6.9008     | 9.9128          | 1     |
| 6.6984     | 10.5699         | 2     |
| 6.0922     | 10.6815         | 3     |
| 7.4481     | 10.2008         | 4     |
| 6.1991     | 10.7918         | 5     |
| 6.0636     | 10.8031         | 6     |
| 6.0324     | 10.8065         | 7     |
| 5.8834     | 11.0328         | 8     |
| 5.6852     | 10.9941         | 9     |
| 5.7602     | 11.4597         | 10    |
| 5.7166     | 11.3688         | 11    |
| 5.6131     | nan             | 12    |
| 5.6185     | 11.7676         | 13    |
| 5.7273     | 11.7161         | 14    |
| 5.6162     | 11.9106         | 15    |
| 5.7344     | 11.9131         | 16    |
| 5.7757     | 11.7448         | 17    |
| 5.6769     | 11.9218         | 18    |
| 5.6946     | 12.1175         | 19    |
| 5.6924     | 12.1778         | 20    |
| 5.5770     | 12.3167         | 21    |
| 5.4709     | 12.4586         | 22    |
| 5.7594     | 11.9413         | 23    |
| 5.5429     | 12.1610         | 24    |
| 5.4948     | 12.8648         | 25    |
| 5.6066     | 12.5354         | 26    |
| 5.7700     | 12.2591         | 27    |
| 5.6883     | 12.3748         | 28    |
| 5.6293     | 12.6476         | 29    |
| 5.7073     | 12.3106         | 30    |
| 5.6654     | 12.6093         | 31    |
| 5.8030     | 12.9058         | 32    |
| 5.5708     | 12.2990         | 33    |
| 5.6817     | 12.7136         | 34    |
| 5.6733     | 12.4783         | 35    |
| 5.5641     | 12.8990         | 36    |
| 5.6529     | 12.8055         | 37    |
| 5.6624     | 12.6477         | 38    |
| 5.7040     | 12.8407         | 39    |
| 5.6736     | 13.3960         | 40    |
| 5.6500     | 12.9211         | 41    |
| 5.6443     | 12.8308         | 42    |
| 5.5996     | 12.8930         | 43    |
| 5.3710     | 13.4719         | 44    |
| 5.5483     | 13.1366         | 45    |
| 5.5923     | 12.8598         | 46    |
| 5.5535     | 13.5748         | 47    |
| 5.5364     | 13.1579         | 48    |
| 5.7182     | 12.7962         | 49    |
| 5.4856     | 13.0038         | 50    |
| 5.5241     | 12.9632         | 51    |
| 5.4996     | 12.8477         | 52    |
| 5.6620     | 12.8107         | 53    |
| 5.6451     | 13.1976         | 54    |
| 5.5493     | 13.3731         | 55    |
| 5.5629     | 13.1022         | 56    |
| 5.6177     | 12.9348         | 57    |
| 5.6781     | 13.0553         | 58    |
| 5.6112     | 13.2850         | 59    |
| 5.5908     | 13.5602         | 60    |
| 5.6984     | 13.0039         | 61    |
| 5.4979     | 13.9429         | 62    |
| 5.6750     | 13.1717         | 63    |
| 5.6696     | 13.2127         | 64    |
| 5.6631     | 13.1643         | 65    |
| 5.6421     | 13.2311         | 66    |
| 5.6400     | 13.3191         | 67    |
| 5.6845     | 13.2363         | 68    |
| 5.6620     | 13.1115         | 69    |
| 5.6084     | 13.5133         | 70    |
| 5.4539     | 13.7953         | 71    |
| 5.6143     | 13.3565         | 72    |
| 5.6153     | 13.1141         | 73    |
| 5.6301     | 13.8310         | 74    |
| 5.7122     | 13.3998         | 75    |
| 5.5747     | 13.4063         | 76    |
| 5.5796     | 13.6303         | 77    |
| 5.5496     | 13.7870         | 78    |
| 5.5954     | 13.6211         | 79    |
| 5.6439     | 13.4964         | 80    |
| 5.7678     | 13.8165         | 81    |
| 5.5670     | 14.0257         | 82    |
| 5.5355     | 14.0359         | 83    |
| 5.6323     | 13.9998         | 84    |
| 5.5381     | nan             | 85    |
| 5.6362     | 13.5828         | 86    |
| 5.6429     | 13.8217         | 87    |
| 5.5660     | 13.5157         | 88    |
| 5.5396     | 14.1864         | 89    |
| 5.5623     | 13.9653         | 90    |
| 5.6208     | 14.1349         | 91    |
| 5.5999     | 13.5511         | 92    |
| 5.6587     | 13.8928         | 93    |
| 5.6402     | 13.6646         | 94    |
| 5.6468     | 13.5333         | 95    |
| 5.5499     | 14.1628         | 96    |
| 5.5621     | 14.3442         | 97    |
| 5.5201     | 14.1347         | 98    |
| 5.5798     | 14.1522         | 99    |


### 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-bert-base-100", "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-bert-base-100
========================


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


* Train Loss: 5.5798
* Validation Loss: 14.1522
* 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': '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