David-ger/fosh-detector-bert-v2.1-with-augmentation

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fosh-detector-bert-v2.1-with-augmentation

This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0311
• —Accuracy: 0.9926
• —Precision: 0.9475
• —Recall: 0.9559
• —F1: 0.9517

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: 5e-05
• —trainbatchsize: 128
• —evalbatchsize: 128
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.50.3
• —Pytorch 2.6.0+cu124
• —Datasets 3.3.2
• —Tokenizers 0.21.1