
# sahajBERT News Category Classification

## Model description

You can embed local or remote images using `![](...)`

## Intended uses & limitations

#### How to use

```python
# You can include sample code which will be formatted
```

#### Limitations and bias

Provide examples of latent issues and potential remediations.

## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.

## Training procedure

### Collaborative training procedure

[here](https://huggingface.co/albertvillanova)

### 
Preprocessing, hardware used, hyperparameters...

## Eval results

### BibTeX entry and citation info

```bibtex
@inproceedings{...,
  year={2020}
}
```
{"language": [], "tags": [], "datasets": [], "metrics": []}
transformers pytorch albert pretraining endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #pretraining #endpoints_compatible #region-us 


# sahajBERT News Category Classification

## Model description

You can embed local or remote images using '![](...)'

## Intended uses & limitations

#### How to use



#### Limitations and bias

Provide examples of latent issues and potential remediations.

## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.

## Training procedure

### Collaborative training procedure

here

### 
Preprocessing, hardware used, hyperparameters...

## Eval results

### BibTeX entry and citation info


# sahajBERT News Category Classification ## Model description

You can embed local or remote images using '![](...)' ## Intended uses & limitations #### How to use #### Limitations and bias

Provide examples of latent issues and potential remediations. ## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data. ## Training procedure ### Collaborative training procedure

here ### 
Preprocessing, hardware used, hyperparameters... ## Eval results ### BibTeX entry and citation info
TAGS
#transformers #pytorch #albert #pretraining #endpoints_compatible #region-us 
 # sahajBERT News Category Classification ## Model description

You can embed local or remote images using '![](...)' ## Intended uses & limitations #### How to use #### Limitations and bias

Provide examples of latent issues and potential remediations. ## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data. ## Training procedure ### Collaborative training procedure

here ### 
Preprocessing, hardware used, hyperparameters... ## Eval results ### BibTeX entry and citation info
passage: TAGS
#transformers #pytorch #albert #pretraining #endpoints_compatible #region-us 
# sahajBERT News Category Classification## Model description

You can embed local or remote images using '![](...)'## Intended uses & limitations#### How to use#### Limitations and bias

Provide examples of latent issues and potential remediations.## Training data

Describe the data you used to train the model.
If you initialized it with pre-trained weights, add a link to the pre-trained model card or repository with description of the pre-training data.## Training procedure### Collaborative training procedure

here### 
Preprocessing, hardware used, hyperparameters...## Eval results### BibTeX entry and citation info