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# bert-base-uncased-multi-128

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7101

## 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: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.6636        | 1.0   | 812   | 3.2325          |
| 3.2963        | 2.0   | 1624  | 3.1937          |
| 3.1132        | 3.0   | 2436  | 3.2984          |
| 2.9386        | 4.0   | 3248  | 3.2430          |
| 2.7742        | 5.0   | 4060  | 3.1272          |
| 2.5954        | 6.0   | 4872  | 3.1778          |
| 2.501         | 7.0   | 5684  | 3.1649          |
| 2.4073        | 8.0   | 6496  | 2.9395          |
| 2.2933        | 9.0   | 7308  | 3.1262          |
| 2.2218        | 10.0  | 8120  | 2.9994          |
| 2.1558        | 11.0  | 8932  | 2.9922          |
| 2.0873        | 12.0  | 9744  | 2.8414          |
| 2.0104        | 13.0  | 10556 | 2.9351          |
| 1.9364        | 14.0  | 11368 | 2.9253          |
| 1.9045        | 15.0  | 12180 | 2.8701          |
| 1.9152        | 16.0  | 12992 | 2.7101          |


### Framework versions

- Transformers 4.8.2
- Pytorch 1.7.1
- Datasets 1.16.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": [], "model_index": [{"name": "bert-base-uncased-multi-128", "results": [{"task": {"name": "Masked Language Modeling", "type": "fill-mask"}}]}]}
transformers pytorch bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-base-uncased-multi-128
===========================


This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.7101


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: 8
* 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 4.8.2
* Pytorch 1.7.1
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* 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 4.8.2
* Pytorch 1.7.1
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* 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 4.8.2
* Pytorch 1.7.1
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* 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 4.8.2
* Pytorch 1.7.1
* Datasets 1.16.1
* Tokenizers 0.10.3