|
---
|
|
tags:
|
|
- "transformers"
|
|
- "text-classification"
|
|
languages: "es"
|
|
license: "apache-2.0"
|
|
---
|
|
|
|
# Unam_tesis_beto_finnetuning: Unam's thesis classification with BETO
|
|
|
|
This model is created from the finetuning of the pre-model
|
|
for Spanish [BETO] (https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased), 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 a text into for five (Psicología, Derecho, Química Farmacéutico Biológica, Actuaría, Economía)
|
|
possible careers at the UNAM.
|
|
|
|
## 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_beto_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('hiiamsid/BETO_es_binary_classification', use_fast=False)
|
|
model = AutoModelForSequenceClassification.from_pretrained(
|
|
'hackathon-pln-e/unam_tesis_BETO_finnetuning', num_labels=5, output_attentions=False,
|
|
output_hidden_states=False)
|
|
pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
|
|
|
|
classificationResult = pipe("Análisis de las condiciones del aprendizaje desde casa en los alumnos de preescolar y primaria del municipio de Nicolás Romero")
|
|
|
|
```
|
|
|
|
To cite this resource in a publication please use the following:
|
|
|
|
## Citation
|
|
|
|
[UNAM's Tesis with BETO finetuning classify] (https://huggingface.co/hackathon-pln-es/unam_tesis_BETO_finnetuning)
|
|
|
|
To cite this resource in a publication please use the following:
|
|
|
|
```
|
|
@inproceedings{SpanishNLPHackaton2022,
|
|
title={UNAM's Theses with BETO fine-tuning 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))
|
|
- Ximena Yeraldin López López ([Ximyer](https://huggingface.co/Ximyer)) |