scideberta-cs-ner

This model is a fine-tuned version of KISTI-AI/scideberta-cs on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1552
• Precision: 0.4943
• Recall: 0.5475
• F1: 0.5195
• Accuracy: 0.9589

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
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	60	0.1980	0.3445	0.2723	0.3042	0.9530
No log	2.0	120	0.1579	0.4444	0.4358	0.4401	0.9582
No log	3.0	180	0.1520	0.4751	0.5321	0.5020	0.9568
No log	4.0	240	0.1518	0.4955	0.5433	0.5183	0.9592
No log	5.0	300	0.1552	0.4943	0.5475	0.5195	0.9589

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu121
• Datasets 2.14.6
• Tokenizers 0.14.1