---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- reddit
metrics:
- f1
- accuracy
model-index:
- name: pretrained_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: reddit
      type: posts
      config: simplified
      split: validation
      args: simplified
    metrics:
    - name: F1
      type: f1
      value: 0.6356
    - name: AUC
      type: auc
      value: 0.7643

---
This model is a fine-tuned version of distilbert-base-uncased on Reddit dataset contains text related to mental health reports of users. it predicts mental health disorders from textual content.

It achieves the following results on the validation set:

* Loss: 0.1873
* F1: 0.6356
* AUC: 0.7643
* Precision: 0.7671

# Description
This model is based on an existing lighter variation of BERT (distilBERT), in order to predict different mental disorders. It does this based on texts or posts (from Reddit) about general experiences of users with mental health problems.
It includes the following classes:

* Borderline
* Anxiety
* Depression
* Bipolar
* OCD
* ADHD
* Schizophrenia
* Asperger
* PTSD

# Training
train size: 90%
val size: 10%

Training set class counts (text samples) after balancing:
Borderline       10398
Anxiety          10393
Depression       10400
Bipolar          10359
OCD              10413
ADHD             10412
Schizophrenia    10447
Asperger         10470
PTSD             10489
dtype: object
Validation set class counts after balancing:
Borderline       1180
Anxiety          1185
Depression       1178
Bipolar          1219
OCD              1165
ADHD             1166
Schizophrenia    1131
Asperger         1108
PTSD             1089

The following hyperparameters were used during training:

model-finetuning: distilbert/distilbert-base-uncased
learning_rate: 1e-5
train_batch_size: 64
val_batch_size: 64
weight_decay: 0.01
optimizer: AdamW
num_epochs: 2-3

# Training results
| Epoch | Training Loss | Validation Loss |
|:-----:|:-------------:|:---------------:|
|: 1.0 :|: 0.2660      :|: 0.2031        :|
|: 2.0 :|: 0.1891      :|: 0.1872        :|

F1 Score: 0.6355
AUC Score: 0.7642

## Classification Report:
Borderline:
 Precision: 0.7606
 Recall: 0.4525
 F1-score: 0.5674
 
Anxiety:
 Precision: 0.7063
 Recall: 0.5459
 F1-score: 0.6158
 
Depression:
 Precision: 0.7286
 Recall: 0.4626
 F1-score: 0.5659
 
Bipolar:
 Precision: 0.7997
 Recall: 0.4487
 F1-score: 0.5748
 
OCD:
 Precision: 0.8222
 Recall: 0.5957
 F1-score: 0.6908
 
ADHD:
 Precision: 0.8856
 Recall: 0.5711
 F1-score: 0.6944
 
Schizophrenia:
 Precision: 0.7540
 Recall: 0.6153
 F1-score: 0.6777
 
Asperger:
 Precision: 0.6743
 Recall: 0.6335
 F1-score: 0.6533
 
PTSD:
 Precision: 0.7724
 Recall: 0.6235
 F1-score: 0.6900