
<!-- 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-m-bert-1

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: 3.3662
- Validation Loss: 14.3784
- 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', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 10.2573    | 10.9396         | 0     |
| 7.8912     | 10.9597         | 1     |
| 6.8354     | 11.2198         | 2     |
| 6.3659     | 11.5487         | 3     |
| 6.0787     | 11.1321         | 4     |
| 5.8528     | 11.1589         | 5     |
| 5.7689     | 11.3702         | 6     |
| 5.3858     | 11.8196         | 7     |
| 5.1194     | 12.0623         | 8     |
| 5.2013     | 11.8812         | 9     |
| 5.0820     | 11.7143         | 10    |
| 4.9735     | 12.6034         | 11    |
| 5.0704     | 11.9522         | 12    |
| 5.0098     | 12.1079         | 13    |
| 5.0869     | 12.2301         | 14    |
| 4.8156     | 12.2691         | 15    |
| 4.8344     | 12.6859         | 16    |
| 4.8416     | 12.5824         | 17    |
| 4.5567     | 13.1279         | 18    |
| 4.6677     | 12.5301         | 19    |
| 4.7248     | 12.5819         | 20    |
| 4.5435     | 12.5466         | 21    |
| 4.6501     | 12.4965         | 22    |
| 4.7348     | 12.7858         | 23    |
| 4.4649     | 12.5727         | 24    |
| 4.3665     | 12.2411         | 25    |
| 4.6434     | 12.6519         | 26    |
| 4.4239     | 13.6048         | 27    |
| 4.3893     | 13.3377         | 28    |
| 4.6514     | 12.3628         | 29    |
| 4.4743     | 12.6613         | 30    |
| 4.2777     | 12.3419         | 31    |
| 4.5667     | 13.5223         | 32    |
| 4.0886     | 13.2224         | 33    |
| 4.3032     | 13.2787         | 34    |
| 4.3670     | 13.1041         | 35    |
| 4.1487     | 12.6903         | 36    |
| 4.3331     | 13.4880         | 37    |
| 4.2907     | 13.2240         | 38    |
| 4.3252     | 12.6439         | 39    |
| 4.1121     | 13.5487         | 40    |
| 4.3273     | 14.4200         | 41    |
| 4.2030     | 14.4691         | 42    |
| 4.1795     | 13.1436         | 43    |
| 4.0424     | 14.0504         | 44    |
| 4.0158     | 12.5468         | 45    |
| 4.0108     | 13.6426         | 46    |
| 3.9515     | 13.4965         | 47    |
| 3.9743     | 13.2319         | 48    |
| 4.1075     | 13.2999         | 49    |
| 4.0501     | 12.7201         | 50    |
| 3.8606     | 13.1704         | 51    |
| 3.8056     | 13.7504         | 52    |
| 3.7682     | 13.5004         | 53    |
| 4.0676     | 13.6444         | 54    |
| 4.0957     | 13.4160         | 55    |
| 4.9373     | 14.2742         | 56    |
| 4.5111     | 13.9469         | 57    |
| 4.1604     | 13.4773         | 58    |
| 3.9956     | 12.9802         | 59    |
| 4.1232     | 14.1715         | 60    |
| 3.9857     | 12.2465         | 61    |
| 4.1082     | 13.8947         | 62    |
| 3.8659     | 13.6370         | 63    |
| 3.8396     | 13.5898         | 64    |
| 3.8220     | 13.2523         | 65    |
| 3.6864     | 13.9323         | 66    |
| 3.7541     | 13.6081         | 67    |
| 3.8218     | 12.9945         | 68    |
| 3.7251     | 13.7039         | 69    |
| 3.5017     | 12.9811         | 70    |
| 3.5342     | 12.5702         | 71    |
| 3.9520     | 12.4899         | 72    |
| 3.7465     | 13.2309         | 73    |
| 3.6003     | 14.0988         | 74    |
| 3.7954     | 13.0785         | 75    |
| 3.5654     | 13.7277         | 76    |
| 3.5591     | 13.7914         | 77    |
| 3.5355     | 13.6749         | 78    |
| 3.5903     | 13.6141         | 79    |
| 3.5371     | 13.4166         | 80    |
| 3.4502     | 12.6523         | 81    |
| 3.3372     | 13.8609         | 82    |
| 3.3071     | 14.3441         | 83    |
| 3.6932     | 13.9718         | 84    |
| 3.5619     | 13.3749         | 85    |
| 3.5016     | 13.1467         | 86    |
| 3.4279     | 14.0124         | 87    |
| 3.3140     | 13.6681         | 88    |
| 3.3575     | 12.9451         | 89    |
| 3.2268     | 12.4299         | 90    |
| 3.2001     | 14.5106         | 91    |
| 3.1390     | 13.9366         | 92    |
| 3.1230     | 13.6865         | 93    |
| 3.2337     | 13.5835         | 94    |
| 3.1397     | 13.8130         | 95    |
| 3.2095     | 13.8431         | 96    |
| 2.9553     | 14.5159         | 97    |
| 3.3319     | 12.9168         | 98    |
| 3.3662     | 14.3784         | 99    |


### Framework versions

- Transformers 4.27.0.dev0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_keras_callback"], "model-index": [{"name": "pretrained-m-bert-1", "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-1
===================


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


* Train Loss: 3.3662
* Validation Loss: 14.3784
* 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', 'learning\_rate': 1e-04, 'decay': 0.0, '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 2.9.2
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* optimizer: {'name': 'Adam', 'learning\_rate': 1e-04, 'decay': 0.0, '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 2.9.2
* 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', 'learning\_rate': 1e-04, 'decay': 0.0, '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 2.9.2
* 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', 'learning\_rate': 1e-04, 'decay': 0.0, '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 2.9.2
* Datasets 2.9.0
* Tokenizers 0.13.2