fdastak/FoodEntity_Hybrid_Lora_Freezing_v1

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FoodEntityHybridLoraFreezingv1

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0060
• —Precision: 0.7778
• —Recall: 0.8509
• —F1: 0.8127
• —Accuracy: 0.9804

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: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 32
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 2
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —PEFT 0.18.0
• —Transformers 4.55.4
• —Pytorch 2.8.0+cpu
• —Datasets 4.0.0
• —Tokenizers 0.21.4