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# bert_12_layer_model_v2_complete_training_new_48_KD_wt_init

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: 231.6032
- Accuracy: 0.4123

## 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: 36
- eval_batch_size: 36
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 606.9724      | 0.06  | 10000  | 581.9434        | 0.1439   |
| 499.7046      | 0.12  | 20000  | 509.0019        | 0.1448   |
| 483.3571      | 0.18  | 30000  | 487.3823        | 0.1451   |
| 374.2657      | 0.25  | 40000  | 364.4415        | 0.2699   |
| 330.4914      | 0.31  | 50000  | 324.6827        | 0.3265   |
| 307.9071      | 0.37  | 60000  | 297.7675        | 0.3516   |
| 293.5813      | 0.43  | 70000  | 284.2744        | 0.3672   |
| 282.876       | 0.49  | 80000  | 271.3589        | 0.3775   |
| 274.4863      | 0.55  | 90000  | 261.3694        | 0.3869   |
| 267.0072      | 0.61  | 100000 | 252.8204        | 0.3939   |
| 259.3755      | 0.68  | 110000 | 247.2895        | 0.3992   |
| 255.5614      | 0.74  | 120000 | 241.0253        | 0.4043   |
| 250.2624      | 0.8   | 130000 | 238.9221        | 0.4085   |
| 245.3816      | 0.86  | 140000 | 231.6032        | 0.4123   |


### 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": "bert_12_layer_model_v2_complete_training_new_48_KD_wt_init", "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\_new\_48\_KD\_wt\_init
=====================================================================


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


* Loss: 231.6032
* Accuracy: 0.4123


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: 36
* eval\_batch\_size: 36
* 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: 36
* eval\_batch\_size: 36
* 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: 36
* eval\_batch\_size: 36
* 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