
# Unam_tesis_ROBERTA_GOB_finnetuning: Unam's thesis classification with PlanTL-GOB-ES/roberta-large-bne


This model is created from the finetuning of the pre-model
for RoBERTa large trained with data from the National Library of Spain (BNE) [
PlanTL-GOB-ES] (https://huggingface.co/PlanTL-GOB-ES/roberta-large-bne), using PyTorch framework, 
and trained with a set of theses of the National Autonomous University of Mexico  [UNAM](https://tesiunam.dgb.unam.mx/F?func=find-b-0&local_base=TES01). 
The model classifies for five (Psicología, Derecho, Química Farmacéutico Biológica, Actuaría, Economía) 
possible careers at the University of Mexico.
List of careers from a text.

## Training Dataset 

1000 documents (Thesis introduction, Author´s first name, Author´s last name, Thesis title, Year, Career )

|     Careers |  Size         | 
|--------------|----------------------|
|  Actuaría   |  200    | 
|  Derecho|   200    | 
|  Economía|   200    | 
|  Psicología|   200    | 
|  Química Farmacéutico Biológica|   200    | 


## Example of use

For further details on how to use unam_tesis_ROBERTA_GOB_finnetuning you can visit the Huggingface Transformers library, starting with the Quickstart section. Unam_tesis models can be accessed simply as 'hackathon-pln-e/unam_tesis_beto_finnetuning' by using the Transformers library. An example of how to download and use the models on this page can be found in this colab notebook. 
```python

 tokenizer = AutoTokenizer.from_pretrained('PlanTL-GOB-ES/roberta-large-bne', use_fast=False)
 model = AutoModelForSequenceClassification.from_pretrained(
                   'hackathon-pln-e/unam_tesis_ROBERTA_GOB_finnetuning', num_labels=5, output_attentions=False,
                  output_hidden_states=False)
 pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
 
 classificationResult = pipe("El objetivo de esta tesis es elaborar un estudio de las condiciones asociadas al aprendizaje desde casa")

```

To cite this resource in a publication please use the following:


## Citation

[UNAM's Tesis with PlanTL-GOB-ES/roberta-large-bne ](https://huggingface.co/hackathon-pln-es/unam_tesis_ROBERTA_GOB_finnetuning)

To cite this resource in a publication please use the following:

```
@inproceedings{SpanishNLPHackaton2022,
  title={Unam's thesis with PlanTL-GOB-ES/roberta-large-bne classify },
  author={López López, Isaac Isaías and López Ramos, Dionis and Clavel Quintero, Yisel and López López, Ximena Yeraldin },
  booktitle={Somos NLP Hackaton 2022},
  year={2022}
}
```


## Team members
- Isaac Isaías López López ([MajorIsaiah](https://huggingface.co/MajorIsaiah))
- Dionis López Ramos ([inoid](https://huggingface.co/inoid))
- Yisel Clavel Quintero ([clavel](https://huggingface.co/clavel))
- Ximyer Yeraldin López López ([Ximyer](https://huggingface.co/Ximyer))

{"license": "apache-2.0"}
license:apache-2.0 region:us
TAGS
#license-apache-2.0 #region-us 

Unam\_tesis\_ROBERTA\_GOB\_finnetuning: Unam's thesis classification with PlanTL-GOB-ES/roberta-large-bne
=========================================================================================================


This model is created from the finetuning of the pre-model
for RoBERTa large trained with data from the National Library of Spain (BNE) [
PlanTL-GOB-ES] (URL using PyTorch framework,
and trained with a set of theses of the National Autonomous University of Mexico UNAM.
The model classifies for five (Psicología, Derecho, Química Farmacéutico Biológica, Actuaría, Economía)
possible careers at the University of Mexico.
List of careers from a text.


Training Dataset
----------------


1000 documents (Thesis introduction, Author´s first name, Author´s last name, Thesis title, Year, Career )



Example of use
--------------


For further details on how to use unam\_tesis\_ROBERTA\_GOB\_finnetuning you can visit the Huggingface Transformers library, starting with the Quickstart section. Unam\_tesis models can be accessed simply as 'hackathon-pln-e/unam\_tesis\_beto\_finnetuning' by using the Transformers library. An example of how to download and use the models on this page can be found in this colab notebook.


To cite this resource in a publication please use the following:


UNAM's Tesis with PlanTL-GOB-ES/roberta-large-bne


To cite this resource in a publication please use the following:


Team members
------------


* Isaac Isaías López López (MajorIsaiah)
* Dionis López Ramos (inoid)
* Yisel Clavel Quintero (clavel)
* Ximyer Yeraldin López López (Ximyer)



TAGS
#license-apache-2.0 #region-us 

passage: TAGS
#license-apache-2.0 #region-us 
