Text Classification
Transformers
Safetensors
Chinese
bert
ai-generated-text-detection
chinese
binary-classification
thesis
academic
Eval Results (legacy)
Instructions to use AnxForever/chinese-ai-detector-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnxForever/chinese-ai-detector-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnxForever/chinese-ai-detector-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnxForever/chinese-ai-detector-bert") model = AutoModelForSequenceClassification.from_pretrained("AnxForever/chinese-ai-detector-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upgrade to v11c boundary-fix (three-set avg 98.56%, independent eval 98.57%, validation 98.75%)
dfd7f4b verified | { | |
| "model": "bert_v11c_boundary_fix", | |
| "per_set": { | |
| "core_v1_test_clean": { | |
| "samples": 545, | |
| "confusion_matrix": [ | |
| [ | |
| 212, | |
| 7 | |
| ], | |
| [ | |
| 4, | |
| 322 | |
| ] | |
| ], | |
| "per_class": { | |
| "Human": { | |
| "precision": 0.9814814814814815, | |
| "recall": 0.9680365296803652, | |
| "f1-score": 0.9747126436781609, | |
| "support": 219.0 | |
| }, | |
| "AI": { | |
| "precision": 0.9787234042553191, | |
| "recall": 0.9877300613496932, | |
| "f1-score": 0.983206106870229, | |
| "support": 326.0 | |
| }, | |
| "accuracy": 0.9798165137614679, | |
| "macro avg": { | |
| "precision": 0.9801024428684003, | |
| "recall": 0.9778832955150292, | |
| "f1-score": 0.978959375274195, | |
| "support": 545.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9798316958379424, | |
| "recall": 0.9798165137614679, | |
| "f1-score": 0.9797931372572696, | |
| "support": 545.0 | |
| } | |
| } | |
| }, | |
| "independent_data": { | |
| "samples": 910, | |
| "confusion_matrix": [ | |
| [ | |
| 749, | |
| 11 | |
| ], | |
| [ | |
| 2, | |
| 148 | |
| ] | |
| ], | |
| "per_class": { | |
| "Human": { | |
| "precision": 0.9973368841544608, | |
| "recall": 0.9855263157894737, | |
| "f1-score": 0.9913964262078094, | |
| "support": 760.0 | |
| }, | |
| "AI": { | |
| "precision": 0.9308176100628931, | |
| "recall": 0.9866666666666667, | |
| "f1-score": 0.9579288025889967, | |
| "support": 150.0 | |
| }, | |
| "accuracy": 0.9857142857142858, | |
| "macro avg": { | |
| "precision": 0.9640772471086769, | |
| "recall": 0.9860964912280702, | |
| "f1-score": 0.9746626143984031, | |
| "support": 910.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9863721686448617, | |
| "recall": 0.9857142857142858, | |
| "f1-score": 0.9858797849519612, | |
| "support": 910.0 | |
| } | |
| } | |
| }, | |
| "merged_v2_val_clean": { | |
| "samples": 1144, | |
| "confusion_matrix": [ | |
| [ | |
| 625, | |
| 10 | |
| ], | |
| [ | |
| 0, | |
| 509 | |
| ] | |
| ], | |
| "per_class": { | |
| "Human": { | |
| "precision": 1.0, | |
| "recall": 0.984251968503937, | |
| "f1-score": 0.9920634920634921, | |
| "support": 635.0 | |
| }, | |
| "AI": { | |
| "precision": 0.9807321772639692, | |
| "recall": 1.0, | |
| "f1-score": 0.9902723735408561, | |
| "support": 509.0 | |
| }, | |
| "accuracy": 0.9912587412587412, | |
| "macro avg": { | |
| "precision": 0.9903660886319846, | |
| "recall": 0.9921259842519685, | |
| "f1-score": 0.9911679328021741, | |
| "support": 1144.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9914271662826577, | |
| "recall": 0.9912587412587412, | |
| "f1-score": 0.9912665695739628, | |
| "support": 1144.0 | |
| } | |
| } | |
| } | |
| }, | |
| "aggregated": { | |
| "samples": 2599, | |
| "confusion_matrix": [ | |
| [ | |
| 1586, | |
| 28 | |
| ], | |
| [ | |
| 6, | |
| 979 | |
| ] | |
| ], | |
| "per_class": { | |
| "Human": { | |
| "precision": 0.9962311557788944, | |
| "recall": 0.9826517967781908, | |
| "f1-score": 0.9893948845913911, | |
| "support": 1614.0 | |
| }, | |
| "AI": { | |
| "precision": 0.9721946375372393, | |
| "recall": 0.9939086294416244, | |
| "f1-score": 0.9829317269076305, | |
| "support": 985.0 | |
| }, | |
| "accuracy": 0.9869180454020777, | |
| "macro avg": { | |
| "precision": 0.9842128966580669, | |
| "recall": 0.9882802131099075, | |
| "f1-score": 0.9861633057495108, | |
| "support": 2599.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.9871215095811144, | |
| "recall": 0.9869180454020777, | |
| "f1-score": 0.9869454000517589, | |
| "support": 2599.0 | |
| } | |
| } | |
| } | |
| } |