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README.md

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+---
+language: en
+license: mit
+tags:
+  - text-classification
+  - depression
+  - mental-health
+  - huggingface
+datasets:
+  - thePixel42/depression-detection
+  - infamouscoder/depression-reddit-cleaned
+model-index:
+  - name: DistilBERT for Depression Detection
+    results:
+      - task:
+          name: Text Classification
+          type: text-classification
+        metrics:
+          - name: Evaluation Loss
+            type: loss
+            value: 0.0631
+---
+
+# DistilBERT for Depression Detection
+
+This model is a fine-tuned version of `distilbert-base-uncased` for binary depression classification based on Reddit and mental health-related posts.
+
+## 📊 Training Details
+
+- **Base model**: distilbert-base-uncased
+- **Epochs**: 3
+- **Batch size**: 8 (train), 16 (eval)
+- **Optimizer**: AdamW with weight decay
+- **Loss function**: CrossEntropyLoss
+- **Hardware**: Trained using GPU acceleration
+
+## 🧾 Datasets Used
+
+- [thePixel42/depression-detection](https://huggingface.co/datasets/thePixel42/depression-detection)
+- [infamouscoder/depression-reddit-cleaned](https://www.kaggle.com/datasets/infamouscoder/depression-reddit-cleaned)
+
+The datasets were cleaned to remove rows with missing `text`, labels were binarized (0 = not depressed, 1 = depressed), and duplicates were removed.
+
+## 🧪 Evaluation
+
+| Metric              | Value     |
+|---------------------|-----------|
+| Loss                | 0.0631    |
+| Samples/sec         | 85.56     |
+| Steps/sec           | 5.35      |
+
+## 🚀 Usage
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+model = AutoModelForSequenceClassification.from_pretrained("your-username/depression-detection-model")
+tokenizer = AutoTokenizer.from_pretrained("your-username/depression-detection-model")
+
+inputs = tokenizer("I feel sad and hopeless", return_tensors="pt")
+with torch.no_grad():
+    logits = model(**inputs).logits
+    predicted_class = torch.argmax(logits).item()
+
+print("Prediction:", predicted_class)

config.json

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+{
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "initializer_range": 0.02,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:076a8d27d2ee6b9e53210d4a40d6a5fc2d3b46eca3d7330b6301d14100169086
+size 267832560

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}