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# bert_12_layer_model_v2_complete_training

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8623
- Accuracy: 0.6328

## 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:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.1798        | 0.11  | 10000  | 6.1719          | 0.1485   |
| 6.0527        | 0.22  | 20000  | 6.0469          | 0.1502   |
| 5.6176        | 0.33  | 30000  | 5.5703          | 0.1772   |
| 3.8786        | 0.44  | 40000  | 3.7441          | 0.3851   |
| 3.4104        | 0.55  | 50000  | 3.3105          | 0.4327   |
| 3.1802        | 0.66  | 60000  | 3.0781          | 0.4601   |
| 3.0115        | 0.76  | 70000  | 2.9141          | 0.4804   |
| 2.8893        | 0.87  | 80000  | 2.7930          | 0.4956   |
| 2.7983        | 0.98  | 90000  | 2.6973          | 0.5081   |
| 2.7039        | 1.09  | 100000 | 2.6016          | 0.5215   |
| 2.5658        | 1.2   | 110000 | 2.4551          | 0.5448   |
| 2.4846        | 1.31  | 120000 | 2.3730          | 0.5576   |
| 2.4284        | 1.42  | 130000 | 2.3164          | 0.5663   |
| 2.3723        | 1.53  | 140000 | 2.2734          | 0.5726   |
| 2.3382        | 1.64  | 150000 | 2.2344          | 0.5787   |
| 2.3084        | 1.75  | 160000 | 2.2031          | 0.5829   |
| 2.2773        | 1.86  | 170000 | 2.1758          | 0.5872   |
| 2.2492        | 1.97  | 180000 | 2.1484          | 0.5909   |
| 2.2261        | 2.08  | 190000 | 2.1230          | 0.5943   |
| 2.1961        | 2.18  | 200000 | 2.1016          | 0.5976   |
| 2.1838        | 2.29  | 210000 | 2.0820          | 0.6004   |
| 2.164         | 2.4   | 220000 | 2.0645          | 0.6031   |
| 2.1456        | 2.51  | 230000 | 2.0469          | 0.6052   |
| 2.1308        | 2.62  | 240000 | 2.0293          | 0.6080   |
| 2.1161        | 2.73  | 250000 | 2.0137          | 0.6101   |
| 2.1052        | 2.84  | 260000 | 2.0020          | 0.6120   |
| 2.0856        | 2.95  | 270000 | 1.9902          | 0.6142   |
| 2.0743        | 3.06  | 280000 | 1.9775          | 0.6159   |
| 2.0598        | 3.17  | 290000 | 1.9678          | 0.6171   |
| 2.0492        | 3.28  | 300000 | 1.9561          | 0.6190   |
| 2.0395        | 3.39  | 310000 | 1.9453          | 0.6203   |
| 2.0328        | 3.5   | 320000 | 1.9365          | 0.6217   |
| 2.0204        | 3.6   | 330000 | 1.9287          | 0.6230   |
| 2.0142        | 3.71  | 340000 | 1.9199          | 0.6243   |
| 2.0021        | 3.82  | 350000 | 1.9121          | 0.6257   |
| 2.006         | 3.93  | 360000 | 1.9043          | 0.6264   |
| 1.9917        | 4.04  | 370000 | 1.8984          | 0.6274   |
| 1.9881        | 4.15  | 380000 | 1.8916          | 0.6284   |
| 1.9843        | 4.26  | 390000 | 1.8867          | 0.6291   |
| 1.977         | 4.37  | 400000 | 1.8809          | 0.6301   |
| 1.9697        | 4.48  | 410000 | 1.8770          | 0.6306   |
| 1.9655        | 4.59  | 420000 | 1.8740          | 0.6313   |
| 1.9649        | 4.7   | 430000 | 1.8691          | 0.6320   |
| 1.9622        | 4.81  | 440000 | 1.8662          | 0.6324   |
| 1.9539        | 4.92  | 450000 | 1.8623          | 0.6328   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert_12_layer_model_v2_complete_training", "results": []}]}
transformers pytorch tensorboard hybridbert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #hybridbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert\_12\_layer\_model\_v2\_complete\_training
==============================================


This model is a fine-tuned version of [](URL on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.8623
* Accuracy: 0.6328


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:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #hybridbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #hybridbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 10
* distributed\_type: multi-GPU
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10000
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.10.1
* Tokenizers 0.13.2