CeLLaTe-ner-2class-reinitllrd-tapt-pubmedbert-tokenizer-adapted-combData-gazetteers-lr_3.36e5

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CeLLaTe-ner-2class-reinitllrd-tapt-pubmedbert-tokenizer-adapted-combData-gazetteers-lr_3.36e5

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

• Loss: 0.1191
• Precision: 0.7710
• Recall: 0.7715
• Micro F1: 0.7713
• Weighted F1: 0.7716
• Macro F1: 0.7796
• Accuracy: 0.9840

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: 3.3553919637731326e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 17
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.01
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Framework versions

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