Model Description
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne to detect suicidal ideation/behavior in public comments (reddit, forums, twitter, etc.) using the Spanish language.
How to use
>>> from transformers import pipeline
>>> model_name= 'hackathon-somos-nlp-2023/roberta-base-bne-finetuned-suicide-es'
>>> pipe = pipeline("text-classification", model=model_name)
>>> pipe("Quiero acabar con todo. No merece la pena vivir.")
[{'label': 'Suicide', 'score': 0.9999703168869019}]
>>> pipe("El partido de fútbol fue igualado, disfrutamos mucho jugando juntos.")
[{'label': 'Non-Suicide', 'score': 0.999990701675415}]
Training
Training data
The dataset consists of comments on Reddit, Twitter, and inputs/outputs of the Alpaca dataset translated to Spanish language and classified as suicidal ideation/behavior and non-suicidal.
The dataset has 10050 rows (777 considered as Suicidal Ideation/Behavior and 9273 considered Non-Suicidal).
More info: https://huggingface.co/datasets/hackathon-somos-nlp-2023/suicide-comments-es
Training procedure
The training data has been tokenized using the PlanTL-GOB-ES/roberta-base-bne tokenizer with a vocabulary size of 50262 tokens and a model maximum length of 512 tokens.
The training lasted a total of 10 minutes using a NVIDIA GPU GeForce RTX 3090 provided by Q Blocks.
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 3090 Off | 00000000:68:00.0 Off | N/A |
| 31% 50C P8 25W / 250W | 1MiB / 24265MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Considerations for Using the Model
The model is designed for use in Spanish language, specifically to detect suicidal ideation/behavior.
Limitations
It is a research toy project. Don't expect a professional, bug-free model. We have found some false positives and false negatives. If you find a bug, please send us your feedback.
Bias
No measures have been taken to estimate the bias and toxicity embedded in the model or dataset. However, the model was fine-tuned using a dataset mainly collected on Reddit, Twitter, and ChatGPT. So there is probably an age bias because the Internet is used more by younger people.
In addition, this model inherits biases from its original base model. You can review these biases by visiting the following link.
Evaluation
Metric
F1 = 2 * (precision * recall) / (precision + recall)
5 K fold
We use KFold with n_splits=5 to evaluate the model.
Results:
>>> best_f1_model_by_fold = [0.9163879598662207, 0.9380530973451328, 0.9333333333333333, 0.8943661971830986, 0.9226190476190477]
>>> best_f1_model_by_fold.mean()
0.9209519270693666
Additional Information
Team
Licesing
This work is licensed under a Apache License, Version 2.0
Demo (Space)
https://huggingface.co/spaces/hackathon-somos-nlp-2023/suicide-comments-es
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