
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BERTUncased_Fake_news_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0027
- Accuracy: 0.9997
- F1: 0.9998
- Percision: 0.9995

## 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: 3e-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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Percision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.0081        | 1.0   | 3865 | 0.0000          | 1.0      | 1.0    | 1.0       |
| 0.0015        | 2.0   | 7730 | 0.0027          | 0.9997   | 0.9998 | 0.9995    |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "widget": [{"text": "Cop Shares Racist Meme About Michelle Obama; Now That Cop Is Having A VERY Bad Day (IMAGES)After the election of Donald Trump many folks seem to see it as a permission slip to be as racist and vile as possible. However, here s the thing, you re still going to get called out as racist and vile. And one Alabama police officer just found this out the hard way.According to the Washington Post: Talladega Police Officer Joel Husk was terminated Wednesday for violating the department s social media and code of conduct policies, City Manager Patrick Bryant said. What did he do? So glad you asked: Husk had posted several memes on his Facebook page, including one showing Obama and Melania Trump.  Fluent in Slovenian, English, French, Serbian, and German,  it said over Trump s photo. Over Obama s, it read:  Fluent in Ghetto. Not only that, he posted several extraordinarily racist memes:via Washington Postvia Washington PostAccording to the City Manager, the statements were  deemed to be biased or racially insensitive or derogatory  and because of that, they  have to take action to correct it. If you re going to be a police officer and serve all the public, you can t assume black people standing up for their rights are equivalent to the KKK. That s about the most horrific equivalence imaginable.Also, according to WaPo: Husk, 37, who had been with the department for about two and a half years, had also shared a meme showing President Obama with the words:  Was Dallas a terrorist attack? Yes! Carried out by Obama s own homegrown terrorist group! Which is a blatant lie and anyone who were to feel that way belongs nowhere near law enforcement. The city took the proper action letting this racist cop go, and hopefully it will be an example to police departments all over the country that this sort of behavior simply cannot be tolerated.Trump s election must not be allowed to serve as a permission slip to bigots everywhere that it s fine to be as awful as possible, because here in the land of the free and the home of the brave, everyone is protected. Everyone, regardless of color, class, gender, sexual orientation, or creed.Featured Photo by Chip Somodevilla/Getty Images", "example_title": "Fake"}, {"text": "Several homes have been evacuated as firefighters tackle a fire at an industrial building in Mansfield. Nottinghamshire Fire and Rescue Service said it was called to a building in Forest Road shortly before 15:45 GMT on Saturday.The service said it received a large number of calls from the public to report smoke coming from the area. An evacuation centre had been opened at a leisure centre in the town for residents waiting to be allowed home. More than 100 firefighters from 16 crews have been involved in the operation, with Nottingham Road, Forest Road and Sandhurst Avenue closed and several properties evacuated. Bus services have also been diverting from the area. Ch Insp Amy Styles-Jones, from Nottinghamshire Police, said: \u2018Thankfully there are no reports of any injuries but neighbouring streets have been evacuated as a precaution.\u2019\u2018The Oak Tree Leisure Centre, in Jubilee Way South, will open from 19:00 as a place of safety for members of the public affected by the fire.\u2018This incident is likely to be ongoing for some time so please avoid the area if possible.\u2019", "example_title": "True"}], "model-index": [{"name": "BERTUncased_Fake_news_classification", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

BERTUncased\_Fake\_news\_classification
=======================================


This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0027
* Accuracy: 0.9997
* F1: 0.9998
* Percision: 0.9995


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: 3e-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: 2


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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: 2 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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: 2 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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: 2### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2