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# bert-base-uncased-issues-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: 1.2312

## 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: 128
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3399        | 1.0   | 73   | 1.7462          |
| 1.799         | 2.0   | 146  | 1.4703          |
| 1.6353        | 3.0   | 219  | 1.4796          |
| 1.5464        | 4.0   | 292  | 1.3851          |
| 1.4697        | 5.0   | 365  | 1.3032          |
| 1.4146        | 6.0   | 438  | 1.3339          |
| 1.3677        | 7.0   | 511  | 1.3349          |
| 1.3345        | 8.0   | 584  | 1.2818          |
| 1.3053        | 9.0   | 657  | 1.2646          |
| 1.2886        | 10.0  | 730  | 1.2355          |
| 1.278         | 11.0  | 803  | 1.3037          |
| 1.2568        | 12.0  | 876  | 1.1511          |
| 1.2399        | 13.0  | 949  | 1.2578          |
| 1.2369        | 14.0  | 1022 | 1.2487          |
| 1.2165        | 15.0  | 1095 | 1.2581          |
| 1.2289        | 16.0  | 1168 | 1.2312          |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.11.0+cu113
- Datasets 2.7.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-issues-128", "results": []}]}
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-issues-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: 1.2312


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: 128
* eval\_batch\_size: 32
* 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 4.21.3
* Pytorch 1.11.0+cu113
* Datasets 2.7.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 32
* 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 4.21.3
* Pytorch 1.11.0+cu113
* Datasets 2.7.1
* Tokenizers 0.12.1
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: 128
* eval\_batch\_size: 32
* 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 4.21.3
* Pytorch 1.11.0+cu113
* Datasets 2.7.1
* Tokenizers 0.12.1
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: 128
* eval\_batch\_size: 32
* 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 4.21.3
* Pytorch 1.11.0+cu113
* Datasets 2.7.1
* Tokenizers 0.12.1