Text Classification
Transformers
Safetensors
English
bert
sentiment-analysis
depression
BERT
mental-health
Eval Results (legacy)
text-embeddings-inference
Instructions to use poudel/Depression_and_Non-Depression_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poudel/Depression_and_Non-Depression_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poudel/Depression_and_Non-Depression_Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poudel/Depression_and_Non-Depression_Classifier") model = AutoModelForSequenceClassification.from_pretrained("poudel/Depression_and_Non-Depression_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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#### Training Hyperparameters
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- **Training regime:** fp32
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- **Epochs:** 3
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- **Learning rate:** 5e-5
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- **Batch size:** 16
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