nci-ner-v2

This model is a fine-tuned version of synapti/nci-ner-v2-stage-a on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5857
• Precision: 0.8651
• Recall: 0.9020
• F1: 0.8832

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: 5e-06
• train_batch_size: 16
• eval_batch_size: 32
• seed: 42
• 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: 0.05
• num_epochs: 3
• label_smoothing_factor: 0.05

Training results

Framework versions

• Transformers 4.46.3
• Pytorch 2.10.0+cu128
• Datasets 2.21.0
• Tokenizers 0.20.3