metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
widget:
- text: >-
It's in the back of my mind. I'm not sure I'll be ok. Not sure I can deal
with this. I'll try...I will try. Even though it's hard to see the point.
But...this still isn't off the table.
base_model: distilroberta-base
model-index:
- name: distilroberta-base-finetuned-suicide-depression
results: []
distilroberta-base-finetuned-suicide-depression
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6622
- Accuracy: 0.7158
Model description
Just a POC of a Transformer fine-tuned on SDCNL dataset for suicide (label 1) or depression (label 0) detection in tweets. DO NOT use it in production
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | 214 | 0.6204 | 0.6632 |
| No log | 2.0 | 428 | 0.6622 | 0.7158 |
| 0.5244 | 3.0 | 642 | 0.7312 | 0.6684 |
| 0.5244 | 4.0 | 856 | 0.9711 | 0.7105 |
| 0.2876 | 5.0 | 1070 | 1.1620 | 0.7 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.13.0
- Tokenizers 0.10.3