readme: ---
  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."
  model-index:
  - name: distilroberta-base-finetuned-suicide-depression
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # distilroberta-base-finetuned-suicide-depression
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/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](https://github.com/ayaanzhaque/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
  