Instructions to use Vinuit/SentinelAI-Filter-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vinuit/SentinelAI-Filter-ONNX with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| { | |
| "experiment_id": "bert_dual_head_20260213_060359", | |
| "config": { | |
| "model_name": "bert-base-uncased", | |
| "num_category_classes": 7, | |
| "num_severity_classes": 4, | |
| "batch_size": 16, | |
| "learning_rate": 0.0003, | |
| "num_epochs": 3, | |
| "max_length": 128, | |
| "lora_r": 8, | |
| "lora_alpha": 16, | |
| "lora_dropout": 0.1, | |
| "seed": 42 | |
| }, | |
| "device": "cuda", | |
| "epochs": [ | |
| { | |
| "epoch": 1, | |
| "train_loss": 2.1082094073295594, | |
| "val_loss": 1.4672169902107932, | |
| "val_category_acc": 0.6914285714285714, | |
| "val_severity_acc": 0.7457142857142857 | |
| }, | |
| { | |
| "epoch": 2, | |
| "train_loss": 1.4187353157997131, | |
| "val_loss": 1.252626198259267, | |
| "val_category_acc": 0.7628571428571429, | |
| "val_severity_acc": 0.7771428571428571 | |
| }, | |
| { | |
| "epoch": 3, | |
| "train_loss": 1.2215006688662937, | |
| "val_loss": 1.1916442256082187, | |
| "val_category_acc": 0.7628571428571429, | |
| "val_severity_acc": 0.7828571428571428 | |
| } | |
| ], | |
| "final_test_metrics": { | |
| "loss": 1.1840462291782552, | |
| "category_accuracy": 0.7628571428571429, | |
| "severity_accuracy": 0.7828571428571428 | |
| } | |
| } |