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# bert_12_layer_model_v1_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: 1.7148
- Accuracy: 0.6576

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.1779        | 0.11  | 10000  | 6.1719          | 0.1487   |
| 4.6914        | 0.22  | 20000  | 4.5039          | 0.3178   |
| 3.2325        | 0.33  | 30000  | 3.0977          | 0.4772   |
| 2.831         | 0.44  | 40000  | 2.7266          | 0.5224   |
| 2.6262        | 0.55  | 50000  | 2.5371          | 0.5455   |
| 2.5006        | 0.66  | 60000  | 2.4141          | 0.5614   |
| 2.4062        | 0.76  | 70000  | 2.3242          | 0.5734   |
| 2.3338        | 0.87  | 80000  | 2.2539          | 0.5823   |
| 2.2838        | 0.98  | 90000  | 2.2012          | 0.5894   |
| 2.231         | 1.09  | 100000 | 2.1504          | 0.5959   |
| 2.1903        | 1.2   | 110000 | 2.1133          | 0.6009   |
| 2.1594        | 1.31  | 120000 | 2.0801          | 0.6054   |
| 2.1307        | 1.42  | 130000 | 2.0488          | 0.6095   |
| 2.0948        | 1.53  | 140000 | 2.0234          | 0.6133   |
| 2.0748        | 1.64  | 150000 | 1.9980          | 0.6169   |
| 2.0572        | 1.75  | 160000 | 1.9756          | 0.6195   |
| 2.0359        | 1.86  | 170000 | 1.9551          | 0.6225   |
| 2.0148        | 1.97  | 180000 | 1.9385          | 0.6251   |
| 1.9994        | 2.08  | 190000 | 1.9219          | 0.6274   |
| 1.9769        | 2.18  | 200000 | 1.9043          | 0.6297   |
| 1.9705        | 2.29  | 210000 | 1.8916          | 0.6317   |
| 1.9557        | 2.4   | 220000 | 1.8779          | 0.6338   |
| 1.9407        | 2.51  | 230000 | 1.8643          | 0.6354   |
| 1.9307        | 2.62  | 240000 | 1.8525          | 0.6372   |
| 1.9186        | 2.73  | 250000 | 1.8408          | 0.6388   |
| 1.9114        | 2.84  | 260000 | 1.8320          | 0.6401   |
| 1.896         | 2.95  | 270000 | 1.8213          | 0.6419   |
| 1.8857        | 3.06  | 280000 | 1.8115          | 0.6433   |
| 1.8752        | 3.17  | 290000 | 1.8037          | 0.6443   |
| 1.8662        | 3.28  | 300000 | 1.7949          | 0.6457   |
| 1.8575        | 3.39  | 310000 | 1.7871          | 0.6470   |
| 1.8538        | 3.5   | 320000 | 1.7793          | 0.6478   |
| 1.8426        | 3.6   | 330000 | 1.7734          | 0.6489   |
| 1.8389        | 3.71  | 340000 | 1.7646          | 0.6501   |
| 1.8278        | 3.82  | 350000 | 1.7598          | 0.6511   |
| 1.8319        | 3.93  | 360000 | 1.7529          | 0.6520   |
| 1.8203        | 4.04  | 370000 | 1.7471          | 0.6527   |
| 1.8162        | 4.15  | 380000 | 1.7412          | 0.6536   |
| 1.8113        | 4.26  | 390000 | 1.7373          | 0.6543   |
| 1.8055        | 4.37  | 400000 | 1.7324          | 0.6551   |
| 1.7991        | 4.48  | 410000 | 1.7285          | 0.6556   |
| 1.7965        | 4.59  | 420000 | 1.7246          | 0.6562   |
| 1.7938        | 4.7   | 430000 | 1.7207          | 0.6567   |
| 1.793         | 4.81  | 440000 | 1.7178          | 0.6571   |
| 1.7848        | 4.92  | 450000 | 1.7148          | 0.6576   |


### 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_v1_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\_v1\_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: 1.7148
* Accuracy: 0.6576


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