Suicidal
This text categorization model can predict if a word sequence is suicidal (1) or not (0).
Data
The model was trained on the Suicide and Depression Dataset obtained from Kaggle. The dataset was taken from Reddit and contains 232,074 data divided into two categories: suicide and non-suicide.
Parameters
The model fine-tuning was conducted on 1 epoch, with a batch size of 6, and a learning rate of 0.00001. Due to limited computing resources and time, we were unable to scale up the number of epochs and batch size.
Performance
Following fine-tuning on the mentioned dataset, the model generated the subsequent results:
- Accuracy: 0.9792
- Recall: 0.9788
- Precision: 0.9677
- F1 Score: 0.9732
How to Use
Import the model from the transformers library:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Aryan4/suicidal")
model = AutoModel.from_pretrained("Aryan4/suicidal")
Resources
For more resources, including the source code, please refer to the GitHub repository Aryanstha/suicidal-text-detection.
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