AI가 움직이고 미래가 업데이트됩니다.nci-ner-v2
This model is a fine-tuned version of synapti/nci-ner-v2-staging on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4872 - Precision: 0.8799 - Recall: 0.9043 - F1: 0.8920 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 0.05 - num_epochs: 3 - label_smoothing_factor: 0.05
번역 준비 중입니다. 원문을 표시합니다.
This model is a fine-tuned version of synapti/nci-ner-v2-staging on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4872 - Precision: 0.8799 - Recall: 0.9043 - F1: 0.8920 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 0.05 - num_epochs: 3 - label_smoothing_factor: 0.05