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README.md

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+---
+language: vi
+tags:
+  - vietnamese
+  - text-classification
+  - sentiment-analysis
+  - PhoBERT
+  - transformers
+license: mit
+datasets:
+  - vanhai123/vietnamese-social-comments
+metrics:
+  - accuracy
+  - f1
+model-index:
+  - name: PhoBERT Vietnamese Comment Classifier (4-class)
+    results:
+      - task:
+          type: text-classification
+          name: Text Classification
+        dataset:
+          name: Vietnamese Social Comments
+          type: vanhai123/vietnamese-social-comments
+        metrics:
+          - type: accuracy
+            value: 0.86
+          - type: f1
+            name: f1_macro
+            value: 0.83
+---
+
+
+# 📄 PhoBERT Vietnamese Comment Classifier (4-class)
+
+Đây là mô hình phân loại bình luận tiếng Việt thành 4 nhãn cảm xúc sử dụng `vinai/phobert-base`.
+
+## 🍿️ Các nhãn phân loại
+
+* `positive` – tích cực
+* `negative` – tiêu cực
+* `neutral` – trung lập
+* `toxic` – kích động, phản cảm
+
+## 🧠 Mô hình nền
+
+* **Base model**: [`vinai/phobert-base`](https://huggingface.co/vinai/phobert-base)
+* **Fine-tuned** trên dataset `vanhai123/vietnamese-social-comments` gồm 4,896 bình luận từ TikTok, Facebook, YouTube.
+
+## 🧪 Kết quả đánh giá
+
+* Accuracy: **86%**
+* Macro F1-score: **83%**
+
+## 💻 Sử dụng
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="vanhai123/phobert-vi-comment-4class")
+classifier("Video này thật sự rất bổ ích và thú vị!")
+```
+
+## 📾 Dataset
+
+* [Vietnamese Social Comments dataset](https://huggingface.co/datasets/vanhai123/vietnamese-social-comments)
+
+## 👤 Tác giả
+
+* Hà Văn Hải – [vanhai11203@gmail.com](mailto:vanhai11203@gmail.com)
+* Hugging Face: [vanhai123](https://huggingface.co/vanhai123)
+
+##

added_tokens.json

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+{
+  "<mask>": 64000
+}

config.json

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+{
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 258,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tokenizer_class": "PhobertTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 64001
+}

model.safetensors

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special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "PhobertTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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