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# bert_12_layer_model_v2_complete_training_new_48

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: 3.5669
- Accuracy: 0.4078

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 6.5761        | 0.08  | 10000  | 6.5400          | 0.1270   |
| 6.3285        | 0.16  | 20000  | 6.3050          | 0.1411   |
| 6.2279        | 0.25  | 30000  | 6.2128          | 0.1449   |
| 6.1754        | 0.33  | 40000  | 6.1535          | 0.1478   |
| 6.1291        | 0.41  | 50000  | 6.1181          | 0.1488   |
| 6.1008        | 0.49  | 60000  | 6.0846          | 0.1495   |
| 6.0716        | 0.57  | 70000  | 6.0609          | 0.1504   |
| 5.9041        | 0.66  | 80000  | 5.8688          | 0.1577   |
| 5.7999        | 0.74  | 90000  | 5.7595          | 0.1691   |
| 5.6997        | 0.82  | 100000 | 5.6469          | 0.1828   |
| 5.6002        | 0.9   | 110000 | 5.5358          | 0.1963   |
| 5.4372        | 0.98  | 120000 | 5.3113          | 0.2253   |
| 5.0465        | 1.07  | 130000 | 4.8765          | 0.2743   |
| 4.7373        | 1.15  | 140000 | 4.5536          | 0.3095   |
| 4.3779        | 1.23  | 150000 | 4.2078          | 0.3417   |
| 4.1299        | 1.31  | 160000 | 3.9910          | 0.3630   |
| 3.9585        | 1.39  | 170000 | 3.8347          | 0.3798   |
| 3.8423        | 1.47  | 180000 | 3.7274          | 0.3911   |
| 3.7403        | 1.56  | 190000 | 3.6422          | 0.3996   |
| 3.6767        | 1.64  | 200000 | 3.5669          | 0.4078   |


### Framework versions

- Transformers 4.29.2
- 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", "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
=======================================================


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


* Loss: 3.5669
* Accuracy: 0.4078


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 4.29.2
* 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 4.29.2
* 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 4.29.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3