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# add_bert_12_layer_model_complete_training_new_96

This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new_48](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new_48) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.4112
- Accuracy: 0.1893

## 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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 5.8144        | 0.08  | 10000  | 5.7474          | 0.1593   |
| 5.7889        | 0.16  | 20000  | 5.7204          | 0.1604   |
| 5.6347        | 0.25  | 30000  | 5.6966          | 0.1623   |
| 5.7138        | 0.33  | 40000  | 5.6725          | 0.1636   |
| 5.6769        | 0.41  | 50000  | 5.6518          | 0.1658   |
| 5.6603        | 0.49  | 60000  | 5.6290          | 0.1686   |
| 5.5852        | 0.57  | 70000  | 5.6076          | 0.1707   |
| 5.6607        | 0.66  | 80000  | 5.5906          | 0.1720   |
| 5.5823        | 0.74  | 90000  | 5.5719          | 0.1739   |
| 5.6124        | 0.82  | 100000 | 5.5543          | 0.1759   |
| 5.6478        | 0.9   | 110000 | 5.5358          | 0.1776   |
| 5.4795        | 0.98  | 120000 | 5.5203          | 0.1787   |
| 5.4557        | 1.07  | 130000 | 5.5028          | 0.1804   |
| 5.5585        | 1.15  | 140000 | 5.4923          | 0.1814   |
| 5.6387        | 1.23  | 150000 | 5.4781          | 0.1825   |
| 5.479         | 1.31  | 160000 | 5.4663          | 0.1833   |
| 5.3951        | 1.39  | 170000 | 5.4512          | 0.1851   |
| 5.5062        | 1.47  | 180000 | 5.4411          | 0.1864   |
| 5.4553        | 1.56  | 190000 | 5.4244          | 0.1881   |
| 5.5461        | 1.64  | 200000 | 5.4112          | 0.1893   |


### Framework versions

- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "add_bert_12_layer_model_complete_training_new_96", "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 

add\_bert\_12\_layer\_model\_complete\_training\_new\_96
========================================================


This model is a fine-tuned version of gokuls/add\_bert\_12\_layer\_model\_complete\_training\_new\_48 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 5.4112
* Accuracy: 0.1893


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: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* 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 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* 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 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 1e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* 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 4.30.1
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3