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# pretrained-m-bert-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: 5.7003
- Validation Loss: 15.3566
- 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 |
|:----------:|:---------------:|:-----:|
| 10.2669    | 10.9400         | 0     |
| 7.8880     | 10.8967         | 1     |
| 6.8580     | 11.5024         | 2     |
| 6.4321     | 11.5023         | 3     |
| 6.2235     | 11.2212         | 4     |
| 6.0038     | 11.3128         | 5     |
| 5.9881     | 11.3604         | 6     |
| 5.4409     | 11.6872         | 7     |
| 5.2113     | 11.5379         | 8     |
| 5.2660     | 12.0264         | 9     |
| 5.2330     | 11.7627         | 10    |
| 5.1121     | 12.2919         | 11    |
| 5.2126     | 12.6272         | 12    |
| 5.2086     | 11.3478         | 13    |
| 5.2459     | 12.2183         | 14    |
| 5.0035     | 11.7580         | 15    |
| 4.9613     | 12.4852         | 16    |
| 5.0312     | 12.4627         | 17    |
| 5.0073     | 13.6309         | 18    |
| 5.4284     | 12.7799         | 19    |
| 5.3100     | 12.6417         | 20    |
| 5.0765     | 12.7851         | 21    |
| 5.2276     | 13.3828         | 22    |
| 5.1986     | 12.7421         | 23    |
| 4.8935     | 12.8679         | 24    |
| 4.6959     | 12.9201         | 25    |
| 5.4161     | 13.4416         | 26    |
| 5.2459     | 14.0112         | 27    |
| 5.2781     | 13.2740         | 28    |
| 5.5104     | 12.8646         | 29    |
| 5.5024     | 13.7514         | 30    |
| 5.6284     | 13.7125         | 31    |
| 5.8452     | 13.6332         | 32    |
| 5.5767     | 13.8019         | 33    |
| 5.6444     | 13.4279         | 34    |
| 5.5551     | 13.2666         | 35    |
| 5.5421     | 13.5996         | 36    |
| 5.5246     | 13.1686         | 37    |
| 5.5233     | 13.3788         | 38    |
| 5.6011     | 13.4038         | 39    |
| 5.3695     | 13.5241         | 40    |
| 5.5061     | 13.6035         | 41    |
| 5.4534     | 13.8652         | 42    |
| 5.4222     | 13.4525         | 43    |
| 5.4408     | 13.6572         | 44    |
| 5.6683     | 13.7671         | 45    |
| 5.7137     | 14.1255         | 46    |
| 5.6777     | 14.4026         | 47    |
| 5.6776     | 14.3435         | 48    |
| 5.8337     | 14.3650         | 49    |
| 5.8583     | 14.2897         | 50    |
| 5.6849     | 14.6518         | 51    |
| 5.7112     | 14.5420         | 52    |
| 5.7281     | 13.9947         | 53    |
| 5.9154     | 14.3210         | 54    |
| 5.6742     | 13.8867         | 55    |
| 5.8674     | 14.2819         | 56    |
| 5.7128     | 14.5811         | 57    |
| 5.7091     | 14.2113         | 58    |
| 5.7479     | 14.4418         | 59    |
| 5.7632     | 13.9566         | 60    |
| 5.6443     | 14.1394         | 61    |
| 5.6794     | 14.5981         | 62    |
| 5.6450     | 14.5139         | 63    |
| 5.6935     | 14.3309         | 64    |
| 5.7443     | 14.3540         | 65    |
| 5.7014     | 14.7472         | 66    |
| 5.7407     | 14.4245         | 67    |
| 5.9023     | 14.4602         | 68    |
| 5.9222     | 14.6654         | 69    |
| 5.6813     | 14.3179         | 70    |
| 5.6505     | 14.1670         | 71    |
| 5.8407     | 14.2520         | 72    |
| 5.6683     | 14.1696         | 73    |
| 5.6880     | 15.1198         | 74    |
| 5.8254     | 14.2783         | 75    |
| 5.7758     | 14.5934         | 76    |
| 5.7180     | 14.4779         | 77    |
| 5.7348     | 14.3955         | 78    |
| 5.6680     | 14.0637         | 79    |
| 5.7029     | 14.6120         | 80    |
| 5.7088     | 14.3396         | 81    |
| 5.7215     | 14.5878         | 82    |
| 5.5987     | 15.0465         | 83    |
| 5.7613     | 14.7521         | 84    |
| 5.7670     | 14.9828         | 85    |
| 5.7954     | 14.6714         | 86    |
| 5.6080     | 15.2686         | 87    |
| 5.7493     | 14.8772         | 88    |
| 5.6884     | 14.4567         | 89    |
| 5.6932     | 14.3316         | 90    |
| 5.7152     | 15.2725         | 91    |
| 5.6548     | 15.0855         | 92    |
| 5.6196     | 14.8487         | 93    |
| 5.7889     | 14.7169         | 94    |
| 5.5958     | 14.9320         | 95    |
| 5.7047     | 14.8829         | 96    |
| 5.5637     | 14.8704         | 97    |
| 5.6375     | 14.7917         | 98    |
| 5.7003     | 15.3566         | 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-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-m-bert-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: 5.7003
* Validation Loss: 15.3566
* 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