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# bert-base-uncased-reviews-3

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6955

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5181        | 1.0   | 54   | 1.8039          |
| 1.4081        | 2.0   | 108  | 1.9063          |
| 1.3536        | 3.0   | 162  | 1.8424          |
| 1.3028        | 4.0   | 216  | 1.8455          |
| 1.3154        | 5.0   | 270  | 1.8451          |
| 1.2665        | 6.0   | 324  | 1.9527          |
| 1.2539        | 7.0   | 378  | 1.8361          |
| 1.2688        | 8.0   | 432  | 1.8245          |
| 1.2686        | 9.0   | 486  | 1.7086          |
| 1.3128        | 10.0  | 540  | 1.7384          |
| 1.3215        | 11.0  | 594  | 1.8663          |
| 1.3384        | 12.0  | 648  | 1.7932          |
| 1.3674        | 13.0  | 702  | 1.8267          |
| 1.368         | 14.0  | 756  | 1.6911          |
| 1.401         | 15.0  | 810  | 1.7279          |
| 1.5053        | 16.0  | 864  | 1.6955          |


### Framework versions

- Transformers 4.13.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-reviews-3", "results": []}]}
transformers pytorch bert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

bert-base-uncased-reviews-3
===========================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.6955


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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16


### Training results



### Framework versions


* Transformers 4.13.0
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #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: 32
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 16### Training results### Framework versions


* Transformers 4.13.0
* Pytorch 1.13.1+cu116
* Datasets 2.8.0
* Tokenizers 0.10.3