Epoch 1 - Val Acc: 0.8855

README.md

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+---
+license: mit
+tags:
+- mental-health
+- depression
+- anxiety
+- stress
+language: en
+---
+
+# Mental Health Multiclass Classification
+
+Fine-tuned for Depression/Anxiety/Stress classification.
+
+## Performance
+- Validation Loss: 0.5120
+- Validation Accuracy: 0.8855
+- F1 (Macro): 0.8541
+
+## Usage
+```python
+import torch
+from transformers import AutoTokenizer
+
+model = torch.load("pytorch_model.bin")
+tokenizer = AutoTokenizer.from_pretrained("alfiyahqthz/bert-multiclass-das")
+
+text = "I feel depressed"
+inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+logits = model(inputs['input_ids'], inputs['attention_mask'])
+prediction = logits.argmax(dim=1).item()
+# 0=Depression, 1=Anxiety, 2=Stress
+```

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7c7f780c5f1ded4de62a6744753910f6625f0404011e3b7545a2343a5f9cdb9b
+size 438804815

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}