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
File size: 1,182 Bytes
740f89a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | {
"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
}
} |