---
base_model:
- AIMH/mental-longformer-base-4096
language:
- en
library_name: transformers
license: mit
metrics:
- name: F1 Score
  type: f1
  value: 0.5524
  verified: false
- name: Accuracy
  type: accuracy
  value: 0.6064
  verified: false
- name: Precision
  type: precision
  value: 0.602
  verified: false
- name: Recall
  type: recall
  value: 0.5385
  verified: false
pipeline_tag: text-classification
---

# About This Model

This model is fine-tuned from the checkpoint of [AIMH/mental-longformer-base-4096](https://huggingface.co/AIMH/mental-longformer-base-4096) using [drmuskangarg/CAMS](https://github.com/drmuskangarg/CAMS/) dataset. For more information about the base Longformer model, please visit their [model page](https://huggingface.co/allenai/longformer-base-4096). We used the same configuration as `AIMH/mental-longformer-base-4096` including their tokenizer.

# Usage

If you wish to use my model to infer your dataset or maybe pre-train it further, you can import my model in a Python script/notebook.

```py
from transformers import LongformerTokenizer, LongformerForSequenceClassification

tokenizer = LongformerTokenizer.from_pretrained("aimh/mental-longformer-base-4096")
model = LongformerForSequenceClassification.from_pretrained("stackofsugar/mentallongformer-cams-finetuned")  
```

If you prefer to use the high-level HuggingFace pipeline to make predictions, you can also do it in a Python script/notebook.

```py
from transformers import pipeline

pipe = pipeline("text-classification", model="stackofsugar/mentallongformer-cams-finetuned", tokenizer="aimh/mental-longformer-base-4096")     
```

# More Information

For more information, visit my [GitHub Repo](https://github.com/stackofsugar/depression-causal-analysis).