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# sa_bert_12_layer_model_complete_training_new

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: 7.4351
- Accuracy: 0.0442

## 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: 0.001
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 7.2755        | 0.11  | 10000  | 7.2838          | 0.0466   |
| 7.2773        | 0.22  | 20000  | 7.2702          | 0.0466   |
| 7.2658        | 0.33  | 30000  | 7.2628          | 0.0481   |
| 7.2999        | 0.44  | 40000  | 7.3364          | 0.0469   |
| 7.3           | 0.55  | 50000  | 7.3381          | 0.0470   |
| 7.342         | 0.66  | 60000  | 7.3410          | 0.0477   |
| 7.3392        | 0.76  | 70000  | 7.3417          | 0.0477   |
| 7.3357        | 0.87  | 80000  | 7.3412          | 0.0476   |
| 7.3331        | 0.98  | 90000  | 7.4346          | 0.0442   |
| 7.3351        | 1.09  | 100000 | 7.4346          | 0.0443   |
| 7.3352        | 1.2   | 110000 | 7.4352          | 0.0442   |
| 7.3306        | 1.31  | 120000 | 7.4347          | 0.0442   |
| 7.3281        | 1.42  | 130000 | 7.4351          | 0.0442   |


### 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": "sa_bert_12_layer_model_complete_training_new", "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 

sa\_bert\_12\_layer\_model\_complete\_training\_new
===================================================


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


* Loss: 7.4351
* Accuracy: 0.0442


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: 0.001
* 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 4.29.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* 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 4.29.2
* 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: 0.001
* 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 4.29.2
* Pytorch 1.14.0a0+410ce96
* Datasets 2.12.0
* Tokenizers 0.13.3