EshAhm/sciBERT-RA-Context-Cross-Encoder

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sciBERT-RA-Context-Cross-Encoder

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: 0.8088
• —Accuracy: 0.8608
• —Macro F1: 0.8608
• —Genuine F1: 0.8595
• —Implausible F1: 0.862

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: 16
• —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
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 5.17.0
• —Pytorch 2.11.0+cu130
• —Datasets 4.8.5
• —Tokenizers 0.23.2