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# pretrained-bert-uncased-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: 5.5801
- Validation Loss: 13.6573
- 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', '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 |
|:----------:|:---------------:|:-----:|
| 8.8978     | 9.5686          | 0     |
| 7.0524     | 9.6480          | 1     |
| 6.8578     | 10.5054         | 2     |
| 6.1054     | 10.4137         | 3     |
| 6.1268     | 10.4515         | 4     |
| 5.8614     | 10.4313         | 5     |
| 5.9680     | 10.7224         | 6     |
| 5.7868     | 11.2948         | 7     |
| 5.5465     | 10.7112         | 8     |
| 5.7115     | 10.8543         | 9     |
| 5.7908     | 11.6466         | 10    |
| 5.5664     | 11.5085         | 11    |
| 5.5865     | 11.4894         | 12    |
| 5.6421     | 11.2182         | 13    |
| 5.6626     | 11.4446         | 14    |
| 5.4587     | 11.2814         | 15    |
| 5.5299     | 11.6601         | 16    |
| 5.5408     | 12.0485         | 17    |
| 5.5092     | 11.9469         | 18    |
| 5.6606     | 12.4353         | 19    |
| 5.7420     | 12.7461         | 20    |
| 5.6078     | 12.1650         | 21    |
| 5.6612     | 12.2811         | 22    |
| 5.7503     | 12.4086         | 23    |
| 5.5609     | 12.6149         | 24    |
| 5.4806     | 12.4447         | 25    |
| 5.6898     | 12.8078         | 26    |
| 5.6168     | 12.4649         | 27    |
| 5.6292     | 12.5851         | 28    |
| 5.8481     | 12.5146         | 29    |
| 5.6491     | 12.6358         | 30    |
| 5.5755     | 12.6996         | 31    |
| 5.8218     | 12.7957         | 32    |
| 5.5641     | 13.1650         | 33    |
| 5.6044     | 12.5065         | 34    |
| 5.6762     | 12.3722         | 35    |
| 5.5931     | 12.7162         | 36    |
| 5.5727     | 12.6179         | 37    |
| 5.5761     | 12.9479         | 38    |
| 5.6360     | 13.0610         | 39    |
| 5.4503     | 13.0441         | 40    |
| 5.5689     | 13.1673         | 41    |
| 5.6327     | 13.2184         | 42    |
| 5.5567     | 12.8114         | 43    |
| 5.6322     | 13.1793         | 44    |
| 5.4677     | 13.1324         | 45    |
| 5.5865     | 13.2891         | 46    |
| 5.5352     | 13.5036         | 47    |
| 5.4867     | 13.5010         | 48    |
| 5.6926     | 13.1743         | 49    |
| 5.7545     | 13.1689         | 50    |
| 5.5422     | 13.3362         | 51    |
| 5.6094     | 13.3983         | 52    |
| 5.5993     | 13.3638         | 53    |
| 5.6803     | 13.3884         | 54    |
| 5.6102     | 12.7277         | 55    |
| 5.7204     | 13.1669         | 56    |
| 5.5271     | 13.5684         | 57    |
| 5.5265     | 13.5086         | 58    |
| 5.5679     | 13.8641         | 59    |
| 5.6738     | 13.1735         | 60    |
| 5.5423     | 13.3285         | 61    |
| 5.5020     | 13.6262         | 62    |
| 5.5065     | 13.4765         | 63    |
| 5.5919     | 13.5598         | 64    |
| 5.5684     | 13.1651         | 65    |
| 5.6378     | 13.4781         | 66    |
| 5.6661     | 13.0726         | 67    |
| 5.7996     | 13.6267         | 68    |
| 5.7453     | 13.4608         | 69    |
| 5.5720     | 13.3663         | 70    |
| 5.4926     | 13.6905         | 71    |
| 5.7386     | 13.5941         | 72    |
| 5.6016     | 13.3110         | 73    |
| 5.5905     | 14.0529         | 74    |
| 5.7030     | 13.7322         | 75    |
| 5.6801     | 13.4712         | 76    |
| 5.6202     | 13.7954         | 77    |
| 5.6230     | 13.8177         | 78    |
| 5.6288     | 13.4887         | 79    |
| 5.6207     | 13.5817         | 80    |
| 5.5904     | 13.7643         | 81    |
| 5.6685     | 14.1648         | 82    |
| 5.5031     | 14.1816         | 83    |
| 5.6752     | 13.9170         | 84    |
| 5.6140     | 13.6953         | 85    |
| 5.6929     | 13.4916         | 86    |
| 5.4762     | 13.8740         | 87    |
| 5.6537     | 13.9725         | 88    |
| 5.5801     | 13.6573         | 89    |


### 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-bert-uncased-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-bert-uncased-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: 5.5801
* Validation Loss: 13.6573
* 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', '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