EshAhm/Paper-Matcher-scibert

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Paper-Matcher-scibert

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.6140
• —Accuracy: 0.865
• —Macro F1: 0.865

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: 32
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 75
• —num_epochs: 6
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 5.18.0
• —Pytorch 2.11.0+cu130
• —Datasets 4.8.5
• —Tokenizers 0.23.2