Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-tokenizer-adapted-spanmask-gazetters-lr_2.16

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

CeLLaTe-ner-2class-pubmedbert-tapt-tokenizer-adapted-spanmask-gazetters-lr_2.16

This model is a fine-tuned version of Mardiyyah/CeLLaTe-tapt-pubmedbert-tokenizer-adapted-spanmask on the OTAR3088/CeLLaTe-ner-2class-iob_final dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0961
• —Precision: 0.7974
• —Recall: 0.7480
• —Micro F1: 0.7720
• —Weighted F1: 0.7721
• —Macro F1: 0.7820
• —Accuracy: 0.9845

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: 2.1601722686e-05
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 3407
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.02
• —num_epochs: 20
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.48.2
• —Pytorch 2.4.1+cu121
• —Datasets 3.0.2
• —Tokenizers 0.21.0