leomaurodesenv/bert-base-uncased-nvidia-aegis-v1

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bert-base-uncased-nvidia-aegis-v1

This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3193
• —Accuracy: 0.8647

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 16
• —optimizer: Use adamwtorchfused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 50
• —num_epochs: 10

Training results

Framework versions

• —Transformers 5.2.0
• —Pytorch 2.10.0+cu128
• —Datasets 4.5.0
• —Tokenizers 0.22.2