N1CKNGUYEN/NLI_UniversalClassifier_beta

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nli_classifier

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3715
• —F1 Macro: 0.8526
• —F1 Micro: 0.8656
• —Accuracy Balanced: 0.8527
• —Accuracy: 0.8656
• —Precision Macro: 0.8526
• —Recall Macro: 0.8527
• —Precision Micro: 0.8656
• —Recall Micro: 0.8656

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: 16
• —evalbatchsize: 128
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 64
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.06
• —num_epochs: 2
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.51.3
• —Pytorch 2.5.1+cu124
• —Datasets 3.5.0
• —Tokenizers 0.21.0