metadata
license: apache-2.0
language: es
tags:
- spanish
datasets:
- catalonia_independence
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: catalonia_independence
type: catalonia_independence
args: spanish
metrics:
- name: Accuracy
type: accuracy
value: 0.7880893300248138
- task:
type: text-classification
name: Text Classification
dataset:
name: catalonia_independence
type: catalonia_independence
config: catalan
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.4592039800995025
verified: true
- name: Precision Macro
type: precision
value: 0.6104489964825159
verified: true
- name: Precision Micro
type: precision
value: 0.4592039800995025
verified: true
- name: Precision Weighted
type: precision
value: 0.6167123723406555
verified: true
- name: Recall Macro
type: recall
value: 0.4146479268294389
verified: true
- name: Recall Micro
type: recall
value: 0.4592039800995025
verified: true
- name: Recall Weighted
type: recall
value: 0.4592039800995025
verified: true
- name: F1 Macro
type: f1
value: 0.33416407167650636
verified: true
- name: F1 Micro
type: f1
value: 0.4592039800995025
verified: true
- name: F1 Weighted
type: f1
value: 0.34549318538357193
verified: true
- name: loss
type: loss
value: 3.393402099609375
verified: true
widget:
- text: >-
Junqueras, sobre la decisión judicial sobre Puigdemont: La justicia que
falta en el Estado llega y llegará de Europa
- text: >-
Desconvocada la manifestación del domingo en Barcelona en apoyo a
Puigdemont
roberta-base-bne-finetuned-catalonia-independence-detector
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the catalonia_independence dataset. It achieves the following results on the evaluation set:
- Loss: 0.9415
- Accuracy: 0.7881
Model description
The data was collected over 12 days during February and March of 2019 from tweets posted in Barcelona, and during September of 2018 from tweets posted in the town of Terrassa, Catalonia. Each corpus is annotated with three classes: AGAINST, FAVOR and NEUTRAL, which express the stance towards the target - independence of Catalonia.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 378 | 0.5534 | 0.7558 |
0.6089 | 2.0 | 756 | 0.5315 | 0.7643 |
0.2678 | 3.0 | 1134 | 0.7336 | 0.7816 |
0.0605 | 4.0 | 1512 | 0.8809 | 0.7866 |
0.0605 | 5.0 | 1890 | 0.9415 | 0.7881 |
Model in action 🚀
Fast usage with pipelines:
from transformers import pipeline
model_path = "JonatanGk/roberta-base-bne-finetuned-catalonia-independence-detector"
independence_analysis = pipeline("text-classification", model=model_path, tokenizer=model_path)
independence_analysis(
"Junqueras, sobre la decisión judicial sobre Puigdemont: La justicia que falta en el Estado llega y llegará de Europa"
)
# Output:
[{'label': 'FAVOR', 'score': 0.9936726093292236}]
independence_analysis(
"El desafío independentista queda adormecido, y eso que el Gobierno ha sido muy claro en que su propuesta para Cataluña es una agenda de reencuentro, centrada en inversiones e infraestructuras")
# Output:
[{'label': 'AGAINST', 'score': 0.7508948445320129}]
independence_analysis(
"Desconvocada la manifestación del domingo en Barcelona en apoyo a Puigdemont"
)
# Output:
[{'label': 'NEUTRAL', 'score': 0.9966907501220703}]
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
Citation
Thx to HF.co & @lewtun for Dataset ;)
Special thx to Manuel Romero/@mrm8488 as my mentor & R.C.
Created by Jonatan Luna | LinkedIn